Dynamic changes of Bacterial Microbiomes in Oropharynx during Infection and Recovery of COVID-19 Omicron Variant.

Oropharyngeal microbiomes play a significant role in the susceptibility and severity of COVID-19, yet the role of these microbiomes play for the development of COVID-19 Omicron variant have not been reported. A total of 791 pharyngeal swab samples were prospectively included in this study, including 297 confirmed cases of Omicron variant (CCO), 222 confirmed case of Omicron who recovered (CCOR), 73 confirmed cases of original strain (CCOS) and 199 healthy controls (HC). All samples completed MiSeq sequencing. The results showed that compared with HC, conditional pathogens increased in CCO, while acid-producing bacteria decreased. Based on six optimal oropharyngeal operational taxonomy units (OTUs), we constructed a marker microbial classifier to distinguish between patients with Omicron variant and healthy people, and achieved high diagnostic efficiency in both the discovery queue and the verification queue. At same time, we introduced a group of cross-age infection verification cohort and Omicron variant subtype XBB.1.5 branch, which can be accurately distinguished by this diagnostic model. We also analyzed the characteristics of oropharyngeal microbiomes in two subgroups of Omicron disease group-severity of infection and vaccination times, and found that the change of oropharyngeal microbiomes may affect the severity of the disease and the efficacy of the vaccine. In addition, we found that some genera with significant differences gradually increased or decreased with the recovery of Omicron variant infection. The results of Spearman analysis showed that 27 oropharyngeal OTUs were closely related to 6 clinical indexes in CCO and HC. Finally, we found that the Omicron variant had different characterization of oropharyngeal microbiomes from the original strain. Our research characterizes oropharyngeal microbiomes of Omicron variant cases and rehabilitation cases, successfully constructed and verified the non-invasive diagnostic model of Omicron variant, described the correlation between microbial OTUs and clinical indexes. It was found that the infection of Omicron variant and the infection of original strain have different characteristics of oropharyngeal microbiomes.

Comparative analysis of Spodoptera frugiperda (J. E. Smith) (Lepidoptera, Noctuidae) corn and rice strains microbiota revealed minor changes across life cycle and strain endosymbiont association.

Background: Spodoptera frugiperda (FAW) is a pest that poses a significant threat to corn production worldwide, causing millions of dollars in losses. The species has evolved into two strains (corn and rice) that differ in their genetics, reproductive isolation, and resistance to insecticides and Bacillus thuringiensis endotoxins. The microbiota plays an important role in insects' physiology, nutrient acquisition, and response to chemical and biological controls. Several studies have been carried out on FAW microbiota from larvae guts using laboratory or field samples and a couple of studies have analyzed the corn strain microbiota across its life cycle. This investigation reveals the first comparison between corn strain (CS) and rice strain (RS) of FAW during different developmental insect stages and, more importantly, endosymbiont detection in both strains, highlighting the importance of studying both FAW populations and samples from different stages. Methods: The composition of microbiota during the life cycle of the FAW corn and rice strains was analyzed through high-throughput sequencing of the bacterial 16S rRNA gene using the MiSeq system. Additionally, culture-dependent techniques were used to isolate gut bacteria and the Transcribed Internal Spacer-ITS, 16S rRNA, and gyrB genes were examined to enhance bacterial identification. Results: Richness, diversity, and bacterial composition changed significantly across the life cycle of FAW. Most diversity was observed in eggs and males. Differences in gut microbiota diversity between CS and RS were minor. However, Leuconostoc, A2, Klebsiella, Lachnoclostridium, Spiroplasma, and Mucispirilum were mainly associated with RS and Colidextribacter, Pelomonas, Weissella, and Arsenophonus to CS, suggesting that FAW strains differ in several genera according to the host plant. Firmicutes and Proteobacteria were the dominant phyla during FAW metamorphosis. Illeobacterium, Ralstonia, and Burkholderia exhibited similar abundancies in both strains. Enterococcus was identified as a conserved taxon across the entire FAW life cycle. Microbiota core communities mainly consisted of Enterococcus and Illeobacterium. A positive correlation was found between Spiroplasma with RS (sampled from eggs, larvae, pupae, and adults) and Arsenophonus (sampled from eggs, larvae, and adults) with CS. Enterococcus mundtii was predominant in all developmental stages. Previous studies have suggested its importance in FAW response to B. thuringensis. Our results are relevant for the characterization of FAW corn and rice strains microbiota to develop new strategies for their control. Detection of Arsenophonus in CS and Spiroplasma in RS are promising for the improvement of this pest management, as these bacteria induce male killing and larvae fitness reduction in other Lepidoptera species.

Altered microbiome of serum exosomes in patients with acute and chronic cholecystitis.

BACKGROUND: This study aimed to investigate the differences in the microbiota composition of serum exosomes from patients with acute and chronic cholecystitis. METHOD: Exosomes were isolated from the serum of cholecystitis patients through centrifugation and identified and characterized using transmission electron microscopy and nano-flow cytometry. Microbiota analysis was performed using 16S rRNA sequencing. RESULTS: Compared to patients with chronic cholecystitis, those with acute cholecystitis exhibited lower richness and diversity. Beta diversity analysis revealed significant differences in the microbiota composition between patients with acute and chronic cholecystitis. The relative abundance of Proteobacteria was significantly higher in exosomes from patients with acute cholecystitis, whereas Actinobacteria, Bacteroidetes, and Firmicutes were significantly more abundant in exosomes from patients with chronic cholecystitis. Furthermore, functional predictions of microbial communities using Tax4Fun analysis revealed significant differences in metabolic pathways such as amino acid metabolism, carbohydrate metabolism, and membrane transport between the two patient groups. CONCLUSIONS: This study confirmed the differences in the microbiota composition within serum exosomes of patients with acute and chronic cholecystitis. Serum exosomes could serve as diagnostic indicators for distinguishing acute and chronic cholecystitis.

Saliva­microbiome­derived signatures: expected to become a potential biomarker for pulmonary nodules (MCEPN-1).

BACKGROUND: Oral microbiota imbalance is associated with the progression of various lung diseases, including lung cancer. Pulmonary nodules (PNs) are often considered a critical stage for the early detection of lung cancer; however, the relationship between oral microbiota and PNs remains unknown. METHODS: We conducted a 'Microbiome with pulmonary nodule series study 1' (MCEPN-1) where we compared PN patients and healthy controls (HCs), aiming to identify differences in oral microbiota characteristics and discover potential microbiota biomarkers for non-invasive, radiation-free PNs diagnosis and warning in the future. We performed 16 S rRNA amplicon sequencing on saliva samples from 173 PN patients and 40 HCs to compare the characteristics and functional changes in oral microbiota between the two groups. The random forest algorithm was used to identify PN salivary microbial markers. Biological functions and potential mechanisms of differential genes in saliva samples were preliminarily explored using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Cluster of Orthologous Groups (COG) analyses. RESULTS: The diversity of salivary microorganisms was higher in the PN group than in the HC group. Significant differences were noted in community composition and abundance of oral microorganisms between the two groups. Neisseria, Prevotella, Haemophilus and Actinomyces, Porphyromonas, Fusobacterium, 7M7x, Granulicatella and Selenomonas were the main differential genera between the PN and HC groups. Fusobacterium, Porphyromonas, Parvimonas, Peptostreptococcus and Haemophilus constituted the optimal marker sets (area under curve, AUC = 0.80), which can distinguish between patients with PNs and HCs. Further, the salivary microbiota composition was significantly correlated with age, sex, and smoking history (P < 0.001), but not with personal history of cancer (P > 0.05). Bioinformatics analysis of differential genes showed that patients with PN showed significant enrichment in protein/molecular functions related to immune deficiency and energy metabolisms, such as the cytoskeleton protein RodZ, nicotinamide adenine dinucleotide phosphate dehydrogenase (NADPH) dehydrogenase, major facilitator superfamily transporters and AraC family transcription regulators. CONCLUSIONS: Our study provides the first evidence that the salivary microbiota can serve as potential biomarkers for identifying PN. We observed a significant association between changes in the oral microbiota and PNs, indicating the potential of salivary microbiota as a new non-invasive biomarker for PNs. TRIAL REGISTRATION: Clinical trial registration number: ChiCTR2200062140; Date of registration: 07/25/2022.

A global survey of host, aquatic, and soil microbiomes reveals shared abundance and genomic features between bacterial and fungal generalists.

Environmental change, coupled with alteration in human lifestyles, is profoundly impacting the microbial communities critical to the health of the Earth and its inhabitants. To identify bacteria and fungi that are resistant and susceptible to habitat change, we analyze thousands of genera detected in 1,580 host, soil, and aquatic samples. This large-scale analysis identifies 48 bacterial and 4 fungal genera that are abundant across the three biomes, demonstrating fitness in diverse environmental conditions. Samples containing these generalists have significantly higher alpha diversity. These generalists play a significant role in shaping cross-kingdom community structure, boasting larger genomes with more secondary metabolism and antimicrobial resistance genes. Conversely, 30 bacterial and 19 fungal genera are only found in a single habitat, suggesting a limited ability to adapt to different and changing environments. These findings contribute to our understanding of microbial niche breadth and its consequences for global biodiversity loss.

Vaginal microbiomes show ethnic evolutionary dynamics and positive selection of Lactobacillus adhesins driven by a long-term niche-specific process.

The vaginal microbiome's composition varies among ethnicities. However, the evolutionary landscape of the vaginal microbiome in the multi-ethnic context remains understudied. We perform a systematic evolutionary analysis of 351 vaginal microbiome samples from 35 multi-ethnic pregnant women, in addition to two validation cohorts, totaling 462 samples from 90 women. Microbiome alpha diversity and community state dynamics show strong ethnic signatures. Lactobacillaceae have a higher ratio of non-synonymous to synonymous polymorphism and lower nucleotide diversity than non-Lactobacillaceae in all ethnicities, with a large repertoire of positively selected genes, including the mucin-binding and cell wall anchor genes. These evolutionary dynamics are driven by the long-term evolutionary process unique to the human vaginal niche. Finally, we propose an evolutionary model reflecting the environmental niches of microbes. Our study reveals the extensive ethnic signatures in vaginal microbial ecology and evolution, highlighting the importance of studying the host-microbiome ecosystem from an evolutionary perspective.

Decomposition of Fomes fomentatius fruiting bodies - transition of healthy living fungus into a decayed bacteria-rich habitat is primarily driven by Arthropoda.

Fomes fomentarius is a widespread, wood-rotting fungus of temperate, broadleaved forests. Although the fruiting bodies of F. fomentarius persist for multiple years, little is known about its associated microbiome or how these recalcitrant structures are ultimately decomposed. Here we used metagenomics and metatranscriptomics to analyse the microbial community associated with healthy living and decomposing F. fomentarius fruiting bodies to assess the functional potential of the fruiting body-associated microbiome and to determine the main players involved in fruiting body decomposition. F. fomentarius sequences in the metagenomes were replaced by bacterial sequences as the fruiting body decomposed. Most CAZymes expressed in decomposing fruiting bodies targeted components of the fungal cell wall with almost all chitin-targeting sequences, plus a high proportion of beta-glucan-targeting sequences, belonging to Arthropoda. We suggest that decomposing fruiting bodies of F. fomentarius represent a habitat rich in bacteria, while its decomposition is primarily driven by Arthropoda. Decomposing fruiting bodies thus represent a specific habitat supporting both microorganisms and microfauna.

Meta-analysis of the human upper respiratory tract microbiome reveals robust taxonomic associations with health and disease.

BACKGROUND: The human upper respiratory tract (URT) microbiome, like the gut microbiome, varies across individuals and between health and disease states. However, study-to-study heterogeneity in reported case-control results has made the identification of consistent and generalizable URT-disease associations difficult. RESULTS: In order to address this issue, we assembled 26 independent 16S rRNA gene amplicon sequencing data sets from case-control URT studies, with approximately 2-3 studies per respiratory condition and ten distinct conditions covering common chronic and acute respiratory diseases. We leveraged the healthy control data across studies to investigate URT associations with age, sex, and geographic location, in order to isolate these associations from health and disease states. CONCLUSIONS: We found several robust genus-level associations, across multiple independent studies, with either health or disease status. We identified disease associations specific to a particular respiratory condition and associations general to all conditions. Ultimately, we reveal robust associations between the URT microbiome, health, and disease, which hold across multiple studies and can help guide follow-up work on potential URT microbiome diagnostics and therapeutics.

Endometrial microbiota alteration in female patients with endometrial polyps based on 16S rRNA gene sequencing analysis.

Introduction: The potential role of the endometrial microbiota in the pathogenesis of endometrial polyps (EPs) warrants further investigation, given the current landscape of limited and inconclusive research findings. We aimed to explore the microecological characteristics of the uterine cavity in patients with EPs and investigate the potential of endometrial microbiota species as novel biomarkers for identifying EPs. Methods: Endometrial samples were collected from 225 patients who underwent hysteroscopies, of whom 167 had EPs, whereas 58 had non- hyperproliferative endometrium status. The endometrial microbiota was assessed using 16S rRNA gene sequencing. We characterized the endometrial microbiota and identified microbial biomarkers for predicting EPs. Results: The endometrial microbial diversity and composition were significantly different between the EP and control groups. Predictive functional analyses of the endometrial microbiota demonstrated significant alterations in pathways involved in sphingolipid metabolism, steroid hormone biosynthesis, and apoptosis between the two groups. Moreover, a classification model based on endometrial microbial ASV-based biomarkers along with the presence of abnormal uterine bleeding symptoms achieved powerful classification potential in identifying EPs in both the discovery and validation cohorts. Conclusion: Our study indicates a potential association between altered endometrial microbiota and EPs. Endometrial microbiota-based biomarkers may prove valuable for the diagnosis of EPs. Clinical trial registration: Chinese Clinical Trial Registry (ChiCTR2100052746).

CoCas9 is a compact nuclease from the human microbiome for efficient and precise genome editing.

The expansion of the CRISPR-Cas toolbox is highly needed to accelerate the development of therapies for genetic diseases. Here, through the interrogation of a massively expanded repository of metagenome-assembled genomes, mostly from human microbiomes, we uncover a large variety (n = 17,173) of type II CRISPR-Cas loci. Among these we identify CoCas9, a strongly active and high-fidelity nuclease with reduced molecular size (1004 amino acids) isolated from an uncultivated Collinsella species. CoCas9 is efficiently co-delivered with its sgRNA through adeno associated viral (AAV) vectors, obtaining efficient in vivo editing in the mouse retina. With this study we uncover a collection of previously uncharacterized Cas9 nucleases, including CoCas9, which enriches the genome editing toolbox.

Integrating taxonomic signals from MAGs and contigs improves read annotation and taxonomic profiling of metagenomes.

Metagenomic analysis typically includes read-based taxonomic profiling, assembly, and binning of metagenome-assembled genomes (MAGs). Here we integrate these steps in Read Annotation Tool (RAT), which uses robust taxonomic signals from MAGs and contigs to enhance read annotation. RAT reconstructs taxonomic profiles with high precision and sensitivity, outperforming other state-of-the-art tools. In high-diversity groundwater samples, RAT annotates a large fraction of the metagenomic reads, calling novel taxa at the appropriate, sometimes high taxonomic ranks. Thus, RAT integrative profiling provides an accurate and comprehensive view of the microbiome from shotgun metagenomics data. The package of Contig Annotation Tool (CAT), Bin Annotation Tool (BAT), and RAT is available at https://github.com/MGXlab/CAT_pack (from CAT pack v6.0). The CAT pack now also supports Genome Taxonomy Database (GTDB) annotations.

Vaginal microbiota molecular profiling and diagnostic performance of artificial intelligence-assisted multiplex PCR testing in women with bacterial vaginosis: a single-center experience.

Background: Bacterial vaginosis (BV) is a most common microbiological syndrome. The use of molecular methods, such as multiplex real-time PCR (mPCR) and next-generation sequencing, has revolutionized our understanding of microbial communities. Here, we aimed to use a novel multiplex PCR test to evaluate the microbial composition and dominant lactobacilli in non-pregnant women with BV, and combined with machine learning algorithms to determine its diagnostic significance. Methods: Residual material of 288 samples of vaginal secretions derived from the vagina from healthy women and BV patients that were sent for routine diagnostics was collected and subjected to the mPCR test. Subsequently, Decision tree (DT), random forest (RF), and support vector machine (SVM) hybrid diagnostic models were constructed and validated in a cohort of 99 women that included 74 BV patients and 25 healthy controls, and a separate cohort of 189 women comprising 75 BV patients, 30 intermediate vaginal microbiota subjects and 84 healthy controls, respectively. Results: The rate or abundance of Lactobacillus crispatus and Lactobacillus jensenii were significantly reduced in BV-affected patients when compared with healthy women, while Lactobacillus iners, Gardnerella vaginalis, Atopobium vaginae, BVAB2, Megasphaera type 2, Prevotella bivia, and Mycoplasma hominis were significantly increased. Then the hybrid diagnostic models were constructed and validated by an independent cohort. The model constructed with support vector machine algorithm achieved excellent prediction performance (Area under curve: 0.969, sensitivity: 90.4%, specificity: 96.1%). Moreover, for subjects with a Nugent score of 4 to 6, the SVM-BV model might be more robust and sensitive than the Nugent scoring method. Conclusion: The application of this mPCR test can be effectively used in key vaginal microbiota evaluation in women with BV, intermediate vaginal microbiota, and healthy women. In addition, this test may be used as an alternative to the clinical examination and Nugent scoring method in diagnosing BV.

Human genetic associations of the airway microbiome in chronic obstructive pulmonary disease.

Little is known about the relationships between human genetics and the airway microbiome. Deeply sequenced airway metagenomics, by simultaneously characterizing the microbiome and host genetics, provide a unique opportunity to assess the microbiome-host genetic associations. Here we performed a co-profiling of microbiome and host genetics with the identification of over 5 million single nucleotide polymorphisms (SNPs) through deep metagenomic sequencing in sputum of 99 chronic obstructive pulmonary disease (COPD) and 36 healthy individuals. Host genetic variation was the most significant factor associated with the microbiome except for geography and disease status, with its top 5 principal components accounting for 12.11% of the microbiome variability. Within COPD individuals, 113 SNPs mapped to candidate genes reported as genetically associated with COPD exhibited associations with 29 microbial species and 48 functional modules (P < 1 × 10-5), where Streptococcus salivarius exhibits the strongest association to SNP rs6917641 in TBC1D32 (P = 9.54 × 10-8). Integration of concurrent host transcriptomic data identified correlations between the expression of host genes and their genetically-linked microbiome features, including NUDT1, MAD1L1 and Veillonella parvula, TTLL9 and Stenotrophomonas maltophilia, and LTA4H and Haemophilus influenzae. Mendelian randomization analyses revealed a potential causal link between PARK7 expression and microbial type III secretion system, and a genetically-mediated association between COPD and increased relative abundance of airway Streptococcus intermedius. These results suggest a previously underappreciated role of host genetics in shaping the airway microbiome and provide fresh hypotheses for genetic-based host-microbiome interactions in COPD.

Symbiotic symphony: Understanding host-microbiota dialogues in a spatial context.

Modern precision sequencing techniques have established humans as a holobiont that live in symbiosis with the microbiome. Microbes play an active role throughout the life of a human ranging from metabolism and immunity to disease tolerance. Hence, it is of utmost significance to study the eukaryotic host in conjunction with the microbial antigens to obtain a complete picture of the host-microbiome crosstalk. Previous attempts at profiling host-microbiome interactions have been either superficial or been attempted to catalogue eukaryotic transcriptomic profile and microbial communities in isolation. Additionally, the nature of such immune-microbial interactions is not random but spatially organised. Hence, for a holistic clinical understanding of the interplay between hosts and microbiota, it's imperative to concurrently analyze both microbial and host genetic information, ensuring the preservation of their spatial integrity. Capturing these interactions as a snapshot in time at their site of action has the potential to transform our understanding of how microbes impact human health. In examining early-life microbial impacts, the limited presence of communities compels analysis within reduced biomass frameworks. However, with the advent of spatial transcriptomics we can address this challenge and expand our horizons of understanding these interactions in detail. In the long run, simultaneous spatial profiling of host-microbiome dialogues can have enormous clinical implications especially in gaining mechanistic insights into the disease prognosis of localised infections and inflammation. This review addresses the lacunae in host-microbiome research and highlights the importance of profiling them together to map their interactions while preserving their spatial context.

A generic approach to infer community-level fitness of microbial genes.

The gene content in a metagenomic pool defines the function potential of a microbial community. Natural selection, operating on the level of genomes or genes, shapes the evolution of community functions by enriching some genes while depriving the others. Despite the importance of microbiomes in the environment and health, a general metric to evaluate the community-wide fitness of microbial genes remains lacking. In this work, we adapt the classic neutral model of species and use it to predict how the abundances of different genes will be shaped by selection, regardless of at which level the selection acts. We establish a simple metric that quantitatively infers the average survival capability of each gene in a microbiome. We then experimentally validate the predictions using synthetic communities of barcoded Escherichia coli strains undergoing neutral assembly and competition. We further show that this approach can be applied to publicly available metagenomic datasets to gain insights into the environment-function interplay of natural microbiomes.

The distinctive weathering crust habitat of a High Arctic glacier comprises discrete microbial micro-habitats.

Sunlight penetrates the ice surfaces of glaciers and ice sheets, forming a water-bearing porous ice matrix known as the weathering crust. This crust is home to a significant microbial community. Despite the potential implications of microbial processes in the weathering crust for glacial melting, biogeochemical cycles, and downstream ecosystems, there have been few explorations of its microbial communities. In our study, we used 16S rRNA gene sequencing and shotgun metagenomics of a Svalbard glacier surface catchment to characterise the microbial communities within the weathering crust, their origins and destinies, and the functional potential of the weathering crust metagenome. Our findings reveal that the bacterial community in the weathering crust is distinct from those in upstream and downstream habitats. However, it comprises two separate micro-habitats, each with different taxa and functional categories. The interstitial porewater is dominated by Polaromonas, influenced by the transfer of snowmelt, and exported via meltwater channels. In contrast, the ice matrix is dominated by Hymenobacter, and its metagenome exhibits a diverse range of functional adaptations. Given that the global weathering crust area and the subsequent release of microbes from it are strongly responsive to climate projections for the rest of the century, our results underscore the pressing need to integrate the microbiome of the weathering crust with other communities and processes in glacial ecosystems.

Comprehensive analysis of the microbiome in Apis cerana honey highlights honey as a potential source for the isolation of beneficial bacterial strains.

Background: Honey is a nutritious food made by bees from nectar and sweet deposits of flowering plants and has been used for centuries as a natural remedy for wound healing and other bacterial infections due to its antibacterial properties. Honey contains a diverse community of bacteria, especially probiotic bacteria, that greatly affect the health of bees and their consumers. Therefore, understanding the microorganisms in honey can help to ensure the quality of honey and lead to the identification of potential probiotic bacteria. Methods: Herein, the bacteria community in honey produced by Apis cerana was investigated by applying the next-generation sequencing (NGS) method for the V3-V4 hypervariable regions of the bacterial 16S rRNA gene. In addition, lactic acid bacteria (LAB) in the honey sample were also isolated and screened for in vitro antimicrobial activity. Results: The results showed that the microbiota of A. cerana honey consisted of two major bacterial phyla, Firmicutes (50%; Clostridia, 48.2%) and Proteobacteria (49%; Gammaproteobacteria, 47.7%). Among the 67 identified bacterial genera, the three most predominant genera were beneficial obligate anaerobic bacteria, Lachnospiraceae (48.14%), followed by Gilliamella (26.80%), and Enterobacter (10.16%). Remarkably, among the identified LAB, Lactobacillus kunkeei was found to be the most abundant species. Interestingly, the isolated L. kunkeei strains exhibited antimicrobial activity against some pathogenic bacteria in honeybees, including Klebsiella spp., Escherichia coli, Enterococcus faecalis, Pseudomonas aeruginosa and Staphylococcus aureus. This underscores the potential candidacy of L. kunkeei for developing probiotics for medical use. Taken together, our results provided new insights into the microbiota community in the A. cerana honey in Hanoi, Vietnam, highlighting evidence that honey can be an unexplored source for isolating bacterial strains with potential probiotic applications in honeybees and humans.

Decoding populations in the ocean microbiome.

Understanding the characteristics and structure of populations is fundamental to comprehending ecosystem processes and evolutionary adaptations. While the study of animal and plant populations has spanned a few centuries, microbial populations have been under scientific scrutiny for a considerably shorter period. In the ocean, analyzing the genetic composition of microbial populations and their adaptations to multiple niches can yield important insights into ecosystem function and the microbiome's response to global change. However, microbial populations have remained elusive to the scientific community due to the challenges associated with isolating microorganisms in the laboratory. Today, advancements in large-scale metagenomics and metatranscriptomics facilitate the investigation of populations from many uncultured microbial species directly from their habitats. The knowledge acquired thus far reveals substantial genetic diversity among various microbial species, showcasing distinct patterns of population differentiation and adaptations, and highlighting the significant role of selection in structuring populations. In the coming years, population genomics is expected to significantly increase our understanding of the architecture and functioning of the ocean microbiome, providing insights into its vulnerability or resilience in the face of ongoing global change. Video Abstract.

Investigating the metabolite signature of an altered oral microbiota as a discriminant factor for multiple sclerosis: a pilot study.

In multiple sclerosis (MS), alterations of the gut microbiota lead to inflammation. However, the role of other microbiomes in the body in MS has not been fully elucidated. In a pilot case-controlled study, we carried out simultaneous characterization of faecal and oral microbiota and conducted an in-depth analysis of bacterial alterations associated with MS. Using 16S rRNA sequencing and metabolic inference tools, we compared the oral/faecal microbiota and bacterial metabolism pathways in French MS patients (n = 14) and healthy volunteers (HV, n = 21). A classification model based on metabolite flux balance was established and validated in an independent German cohort (MS n = 12, HV n = 38). Our analysis revealed decreases in diversity indices and oral/faecal compartmentalization, the depletion of commensal bacteria (Aggregatibacter and Streptococcus in saliva and Coprobacter and Roseburia in faeces) and enrichment of inflammation-associated bacteria in MS patients (Leptotrichia and Fusobacterium in saliva and Enterobacteriaceae and Actinomyces in faeces). Several microbial pathways were also altered (the polyamine pathway and remodelling of bacterial surface antigens and energetic metabolism) while flux balance analysis revealed associated alterations in metabolite production in MS (nitrogen and nucleoside). Based on this analysis, we identified a specific oral metabolite signature in MS patients, that could discriminate MS patients from HV and rheumatoid arthritis patients. This signature allowed us to create and validate a discrimination model on an independent cohort, which reached a specificity of 92%. Overall, the oral and faecal microbiomes were altered in MS patients. This pilot study highlights the need to study the oral microbiota and oral health implications in patients with autoimmune diseases on a larger scale and suggests that knowledge of the salivary microbiome could help guide the identification of new pathogenic mechanisms associated with the microbiota in MS patients.

Anna Karenina as a promoter of microbial diversity in the cosmopolitan agricultural pest Zeugodacus cucurbitae (Diptera, Tephritidae).

Gut microbial communities are critical in determining the evolutive success of fruit fly phytophagous pests (Diptera, Tephritidae), facilitating their adaptation to suboptimal environmental conditions and to plant allelochemical defences. An important source of variation for the microbial diversity of fruit flies is represented by the crop on which larvae are feeding. However, a "crop effect" is not always the main driver of microbial patterns, and it is often observed in combination with other and less obvious processes. In this work, we aim at verifying if environmental stress and, by extension, changing environmental conditions, can promote microbial diversity in Zeugodacus cucurbitae (Coquillett), a cosmopolitan pest of cucurbit crops. With this objective, 16S rRNA metabarcoding was used to test differences in the microbial profiles of wild fly populations in a large experimental setup in Eastern Central Tanzania. The analysis of 2,973 unique ASV, which were assigned to 22 bacterial phyla, 221 families and 590 putative genera, show that microbial α diversity (as estimated by Abundance Coverage Estimator, Faith's Phylogenetic Diversity, Shannon-Weiner and the Inverse Simpson indexes) as well as ß microbial diversity (as estimated by Compositional Data analysis of ASVs and of aggregated genera) significantly change as the species gets closer to its altitudinal limits, in farms where pesticides and agrochemicals are used. Most importantly, the multivariate dispersion of microbial patterns is significantly higher in these stressful environmental conditions thus indicating that Anna Karenina effects contribute to the microbial diversity of Z. cucurbitae. The crop effect was comparably weaker and detected as non-consistent changes across the experimental sites. We speculate that the impressive adaptive potential of polyphagous fruit flies is, at least in part, related to the Anna Karenina principle, which promotes stochastic changes in the microbial diversity of fly populations exposed to suboptimal environmental conditions.