Intestinal Blastocystis is linked to healthier diets and more favorable cardiometabolic outcomes in 56,989 individuals from 32 countries.

Diet impacts human health, influencing body adiposity and the risk of developing cardiometabolic diseases. The gut microbiome is a key player in the diet-health axis, but while its bacterial fraction is widely studied, the role of micro-eukaryotes, including Blastocystis, is underexplored. We performed a global-scale analysis on 56,989 metagenomes and showed that human Blastocystis exhibits distinct prevalence patterns linked to geography, lifestyle, and dietary habits. Blastocystis presence defined a specific bacterial signature and was positively associated with more favorable cardiometabolic profiles and negatively with obesity (p < 1e-16) and disorders linked to altered gut ecology (p < 1e-8). In a diet intervention study involving 1,124 individuals, improvements in dietary quality were linked to weight loss and increases in Blastocystis prevalence (p = 0.003) and abundance (p < 1e-7). Our findings suggest a potentially beneficial role for Blastocystis, which may help explain personalized host responses to diet and downstream disease etiopathogenesis.

Unexplored microbial diversity from 2,500 food metagenomes and links with the human microbiome.

Complex microbiomes are part of the food we eat and influence our own microbiome, but their diversity remains largely unexplored. Here, we generated the open access curatedFoodMetagenomicData (cFMD) resource by integrating 1,950 newly sequenced and 583 public food metagenomes. We produced 10,899 metagenome-assembled genomes spanning 1,036 prokaryotic and 108 eukaryotic species-level genome bins (SGBs), including 320 previously undescribed taxa. Food SGBs displayed significant microbial diversity within and between food categories. Extension to >20,000 human metagenomes revealed that food SGBs accounted on average for 3% of the adult gut microbiome. Strain-level analysis highlighted potential instances of food-to-gut transmission and intestinal colonization (e.g., Lacticaseibacillus paracasei) as well as SGBs with divergent genomic structures in food and humans (e.g., Streptococcus gallolyticus and Limosilactobabillus mucosae). The cFMD expands our knowledge on food microbiomes, their role in shaping the human microbiome, and supports future uses of metagenomics for food quality, safety, and authentication.

Extensive Unexplored Human Microbiome Diversity Revealed by Over 150,000 Genomes from Metagenomes Spanning Age, Geography, and Lifestyle.

The body-wide human microbiome plays a role in health, but its full diversity remains uncharacterized, particularly outside of the gut and in international populations. We leveraged 9,428 metagenomes to reconstruct 154,723 microbial genomes (45% of high quality) spanning body sites, ages, countries, and lifestyles. We recapitulated 4,930 species-level genome bins (SGBs), 77% without genomes in public repositories (unknown SGBs [uSGBs]). uSGBs are prevalent (in 93% of well-assembled samples), expand underrepresented phyla, and are enriched in non-Westernized populations (40% of the total SGBs). We annotated 2.85 M genes in SGBs, many associated with conditions including infant development (94,000) or Westernization (106,000). SGBs and uSGBs permit deeper microbiome analyses and increase the average mappability of metagenomic reads from 67.76% to 87.51% in the gut (median 94.26%) and 65.14% to 82.34% in the mouth. We thus identify thousands of microbial genomes from yet-to-be-named species, expand the pangenomes of human-associated microbes, and allow better exploitation of metagenomic technologies.

The person-to-person transmission landscape of the gut and oral microbiomes.

The human microbiome is an integral component of the human body and a co-determinant of several health conditions1,2. However, the extent to which interpersonal relations shape the individual genetic makeup of the microbiome and its transmission within and across populations remains largely unknown3,4. Here, capitalizing on more than 9,700 human metagenomes and computational strain-level profiling, we detected extensive bacterial strain sharing across individuals (more than 10 million instances) with distinct mother-to-infant, intra-household and intra-population transmission patterns. Mother-to-infant gut microbiome transmission was considerable and stable during infancy (around 50% of the same strains among shared species (strain-sharing rate)) and remained detectable at older ages. By contrast, the transmission of the oral microbiome occurred largely horizontally and was enhanced by the duration of cohabitation. There was substantial strain sharing among cohabiting individuals, with 12% and 32% median strain-sharing rates for the gut and oral microbiomes, and time since cohabitation affected strain sharing more than age or genetics did. Bacterial strain sharing additionally recapitulated host population structures better than species-level profiles did. Finally, distinct taxa appeared as efficient spreaders across transmission modes and were associated with different predicted bacterial phenotypes linked with out-of-host survival capabilities. The extent of microorganism transmission that we describe underscores its relevance in human microbiome studies5, especially those on non-infectious, microbiome-associated diseases.

Vitamin A carotenoids, but not retinoids, mediate the impact of a healthy diet on gut microbial diversity.

BACKGROUND: Vitamin A is essential for physiological processes like vision and immunity. Vitamin A's effect on gut microbiome composition, which affects absorption and metabolism of other vitamins, is still unknown. Here we examined the relationship between gut metagenome composition and six vitamin A-related metabolites (two retinoid: -retinol, 4 oxoretinoic acid (oxoRA) and four carotenoid metabolites, including beta-cryptoxanthin and three carotene diols). METHODS: We included 1053 individuals from the TwinsUK cohort with vitamin A-related metabolites measured in serum and faeces, diet history, and gut microbiome composition assessed by shotgun metagenome sequencing. Results were replicated in 327 women from the ZOE PREDICT-1 study. RESULTS: Five vitamin A-related serum metabolites were positively correlated with microbiome alpha diversity (r = 0.15 to r = 0.20, p < 4 × 10-6). Carotenoid compounds were positively correlated with the short-chain fatty-acid-producing bacteria Faecalibacterium prausnitzii and Coprococcus eutactus. Retinol was not associated with any microbial species. We found that gut microbiome composition could predict circulating levels of carotenoids and oxoretinoic acid with AUCs ranging from 0.66 to 0.74 using random forest models, but not retinol (AUC = 0.52). The healthy eating index (HEI) was strongly associated with gut microbiome diversity and with all carotenoid compounds, but not retinoids. We investigated the mediating role of carotenoid compounds on the effect of a healthy diet (HEI) on gut microbiome diversity, finding that carotenoids significantly mediated between 18 and 25% of the effect of HEI on gut microbiome alpha diversity. CONCLUSIONS: Our results show strong links between circulating carotene compounds and gut microbiome composition and potential links to a healthy diet pattern.

Snack quality and snack timing are associated with cardiometabolic blood markers: the ZOE PREDICT study.

BACKGROUND: Snacking is a common diet behaviour which accounts for a large proportion of daily energy intake, making it a key determinant of diet quality. However, the relationship between snacking frequency, quality and timing with cardiometabolic health remains unclear. DESIGN: Demography, diet, health (fasting and postprandial cardiometabolic blood and anthropometrics markers) and stool metagenomics data were assessed in the UK PREDICT 1 cohort (N = 1002) (NCT03479866). Snacks (foods or drinks consumed between main meals) were self-reported (weighed records) across 2-4 days. Average snacking frequency and quality [snack diet index (SDI)] were determined (N = 854 after exclusions). Associations between snacking frequency, quality and timing with cardiometabolic blood and anthropometric markers were assessed using regression models (adjusted for age, sex, BMI, education, physical activity level and main meal quality). RESULTS: Participants were aged (mean, SD) 46.1 ± 11.9 years, had a mean BMI of 25.6 ± 4.88 kg/m2 and were predominantly female (73%). 95% of participants were snackers (≥ 1 snack/day; n = 813); mean daily snack intake was 2.28 snacks/day (24 ± 16% of daily calories; 203 ± 170 kcal); and 44% of participants were discordant for meal and snack quality. In snackers, overall snacking frequency and quantity of snack energy were not associated with cardiometabolic risk markers. However, lower snack quality (SDI range 1-11) was associated with higher blood markers, including elevated fasting triglycerides (TG (mmol/L) ß; - 0.02, P = 0.02), postprandial TGs (6hiAUC (mmol/L.s); ß; - 400, P = 0.01), fasting insulin (mIU/L) (ß; - 0.15, P = 0.04), insulin resistance (HOMA-IR; ß; - 0.04, P = 0.04) and hunger (scale 0-100) (ß; - 0.52, P = 0.02) (P values non-significant after multiple testing adjustments). Late-evening snacking (≥ 9 pm; 31%) was associated with lower blood markers (HbA1c; 5.54 ± 0.42% vs 5.46 ± 0.28%, glucose 2hiAUC; 8212 ± 5559 vs 7321 ± 4928 mmol/L.s, P = 0.01 and TG 6hiAUC; 11,638 ± 8166 vs 9781 ± 6997 mmol/L.s, P = 0.01) compared to all other snacking times (HbA1c remained significant after multiple testing). CONCLUSION: Snack quality and timing of consumption are simple diet features which may be targeted to improve diet quality, with potential health benefits. CLINICAL TRIAL REGISTRY NUMBER AND WEBSITE: NCT03479866, https://clinicaltrials.gov/ct2/show/NCT03479866?term=NCT03479866&draw=2&rank=1.

Recent genetic exchanges and admixture shape the genome and population structure of the zoonotic pathogen Cryptosporidium parvum.

Cryptosporidium parvum is a globally distributed zoonotic pathogen and a major cause of diarrhoeal disease in humans and ruminants. The parasite's life cycle comprises an obligatory sexual phase, during which genetic exchanges can occur between previously isolated lineages. Here, we compare 32 whole genome sequences from human- and ruminant-derived parasite isolates collected across Europe, Egypt and China. We identify three strongly supported clusters that comprise a mix of isolates from different host species, geographic origins, and subtypes. We show that: (1) recombination occurs between ruminant isolates into human isolates; (2) these recombinant regions can be passed on to other human subtypes through gene flow and population admixture; (3) there have been multiple genetic exchanges, and most are probably recent; (4) putative virulence genes are significantly enriched within these genetic exchanges, and (5) this results in an increase in their nucleotide diversity. We carefully dissect the phylogenetic sequence of two genetic exchanges, illustrating the long-term evolutionary consequences of these events. Our results suggest that increased globalization and close human-animal contacts increase the opportunity for genetic exchanges between previously isolated parasite lineages, resulting in spillover and spillback events. We discuss how this can provide a novel substrate for natural selection at genes involved in host-parasite interactions, thereby potentially altering the dynamic coevolutionary equilibrium in the Red Queens arms race.

Exploring the relationship between social jetlag with gut microbial composition, diet and cardiometabolic health, in the ZOE PREDICT 1 cohort.

PURPOSE: In this study, we explore the relationship between social jetlag (SJL), a parameter of circadian misalignment, and gut microbial composition, diet and cardiometabolic health in the ZOE PREDICT 1 cohort (NCT03479866). METHODS: We assessed demographic, diet, cardiometabolic, stool metagenomics and postprandial metabolic measures (n = 1002). We used self-reported habitual sleep (n = 934) to calculate SJL (difference in mid-sleep time point of ≥ 1.5 h on week versus weekend days). We tested group differences (SJL vs no-SJL) in cardiometabolic markers and diet (ANCOVA) adjusting for sex, age, BMI, ethnicity, and socio-economic status. We performed comparisons of gut microbial composition using machine learning and association analyses on the species level genome bins present in at least 20% of the samples. RESULTS: The SJL group (16%, n = 145) had a greater proportion of males (39% vs 25%), shorter sleepers (average sleep < 7 h; 5% vs 3%), and were younger (38.4 ± 11.3y vs 46.8 ± 11.7y) compared to the no-SJL group. SJL was associated with a higher relative abundance of 9 gut bacteria and lower abundance of 8 gut bacteria (q < 0.2 and absolute Cohen's effect size > 0.2), in part mediated by diet. SJL was associated with unfavourable diet quality (less healthful Plant-based Diet Index), higher intakes of potatoes and sugar-sweetened beverages, and lower intakes of fruits, and nuts, and slightly higher markers of inflammation (GlycA and IL-6) compared with no-SJL (P < 0.05 adjusted for covariates); rendered non-significant after multiple testing adjustments. CONCLUSIONS: Novel associations between SJL and a more disadvantageous gut microbiome in a cohort of predominantly adequate sleepers highlight the potential implications of SJL for health.

Blue poo: impact of gut transit time on the gut microbiome using a novel marker.

BACKGROUND AND AIMS: Gut transit time is a key modulator of host-microbiome interactions, yet this is often overlooked, partly because reliable methods are typically expensive or burdensome. The aim of this single-arm, single-blinded intervention study is to assess (1) the relationship between gut transit time and the human gut microbiome, and (2) the utility of the 'blue dye' method as an inexpensive and scalable technique to measure transit time. METHODS: We assessed interactions between the taxonomic and functional potential profiles of the gut microbiome (profiled via shotgun metagenomic sequencing), gut transit time (measured via the blue dye method), cardiometabolic health and diet in 863 healthy individuals from the PREDICT 1 study. RESULTS: We found that gut microbiome taxonomic composition can accurately discriminate between gut transit time classes (0.82 area under the receiver operating characteristic curve) and longer gut transit time is linked with specific microbial species such as Akkermansia muciniphila, Bacteroides spp and Alistipes spp (false discovery rate-adjusted p values <0.01). The blue dye measure of gut transit time had the strongest association with the gut microbiome over typical transit time proxies such as stool consistency and frequency. CONCLUSIONS: Gut transit time, measured via the blue dye method, is a more informative marker of gut microbiome function than traditional measures of stool consistency and frequency. The blue dye method can be applied in large-scale epidemiological studies to advance diet-microbiome-health research. Clinical trial registry website https://clinicaltrials.gov/ct2/show/NCT03479866 and trial number NCT03479866.

High intake of vegetables is linked to lower white blood cell profile and the effect is mediated by the gut microbiome.

BACKGROUND: Chronic inflammation, which can be modulated by diet, is linked to high white blood cell counts and correlates with higher cardiometabolic risk and risk of more severe infections, as in the case of COVID-19. METHODS: Here, we assessed the association between white blood cell profile (lymphocytes, basophils, eosinophils, neutrophils, monocytes and total white blood cells) as markers of chronic inflammation, habitual diet and gut microbiome composition (determined by sequencing of the 16S RNA) in 986 healthy individuals from the PREDICT-1 nutritional intervention study. We then investigated whether the gut microbiome mediates part of the benefits of vegetable intake on lymphocyte counts. RESULTS: Higher levels of white blood cells, lymphocytes and basophils were all significantly correlated with lower habitual intake of vegetables, with vegetable intake explaining between 3.59 and 6.58% of variation in white blood cells after adjusting for covariates and multiple testing using false discovery rate (q < 0.1). No such association was seen with fruit intake. A mediation analysis found that 20.00% of the effect of vegetable intake on lymphocyte counts was mediated by one bacterial genus, Collinsella, known to increase with the intake of processed foods and previously associated with fatty liver disease. We further correlated white blood cells to other inflammatory markers including IL6 and GlycA, fasting and post-prandial glucose levels and found a significant relationship between inflammation and diet. CONCLUSION: A habitual diet high in vegetables, but not fruits, is linked to a lower inflammatory profile for white blood cells, and a fifth of the effect is mediated by the genus Collinsella. TRIAL REGISTRATION: The ClinicalTrials.gov registration identifier is NCT03479866 .

Genes Encoding Microbial Acyl Coenzyme A Binding Protein/Diazepam-Binding Inhibitor Orthologs Are Rare in the Human Gut Microbiome and Show No Links to Obesity.

Acyl coenzyme A (CoA) binding protein (ACBP), also called diazepam-binding inhibitor (DBI), is a phylogenetically conserved protein that is expressed by all eukaryotic species as well as by some bacteria. Since elevated ACBP/DBI levels play a major role in the inhibition of autophagy, increase in appetite, and enhanced lipid storage that accompany obesity, we wondered whether ACBP/DBI produced by the human microbiome might affect host weight. We found that the genomes of bacterial commensals rarely contain ACBP/DBI homologues, which are rather encoded by genomes of some pathogenic or environmental taxa that were not prevalent in human feces. Exhaustive bioinformatic analyses of 1,899 gut samples from healthy individuals refuted the hypothesis that bacterial ACBP/DBI might affect the body mass index (BMI) in a physiological context. Thus, the physiological regulation of BMI is unlikely to be affected by microbial ACBP/DBI-like proteins. However, at the speculative level, it remains possible that ACBP/DBI produced by potential pathogenic bacteria might enhance their virulence by inhibiting autophagy and hence subverting innate immune responses. IMPORTANCE Acyl coenzyme A (CoA) binding protein (ACBP) can be encoded by several organisms across the domains of life, including microbes, and has shown to play major roles in human metabolic processes. However, little is known about its presence in the human gut microbiome and whether its microbial counterpart could also play a role in human metabolism. In the present study, we found that microbial ACBP/DBI sequences were rarely present in the gut microbiome across multiple metagenomic data sets. Microbes that carried ACBP/DBI in the human gut microbiome included Saccharomyces cerevisiae, Lautropia mirabilis, and Comamonas kerstersii, but these microorganisms were not associated with body mass index, further indicating an unconvincing role for microbial ACBP/DBI in human metabolism.

Strain-level microbial epidemiology and population genomics from shotgun metagenomics.

Identifying microbial strains and characterizing their functional potential is essential for pathogen discovery, epidemiology and population genomics. We present pangenome-based phylogenomic analysis (PanPhlAn; http://segatalab.cibio.unitn.it/tools/panphlan), a tool that uses metagenomic data to achieve strain-level microbial profiling resolution. PanPhlAn recognized outbreak strains, produced the largest strain-level population genomic study of human-associated bacteria and, in combination with metatranscriptomics, profiled the transcriptional activity of strains in complex communities.

Machine learning for microbiologists.

Machine learning is increasingly important in microbiology where it is used for tasks such as predicting antibiotic resistance and associating human microbiome features with complex host diseases. The applications in microbiology are quickly expanding and the machine learning tools frequently used in basic and clinical research range from classification and regression to clustering and dimensionality reduction. In this Review, we examine the main machine learning concepts, tasks and applications that are relevant for experimental and clinical microbiologists. We provide the minimal toolbox for a microbiologist to be able to understand, interpret and use machine learning in their experimental and translational activities.

High dietary inflammatory index associates with inflammatory proteins in plasma.

BACKGROUND AND AIM: Unhealthy dietary habits and highly caloric foods induce metabolic alterations and promote the development of the inflammatory consequences of obesity, insulin resistance, diabetes and cardiovascular diseases. Describing an inflammatory effect of diet is difficult to pursue, owing lacks of standardized quali-quantitative dietary assessments. The Dietary Inflammatory Index (DII) has been proposed as an estimator of the pro- or anti-inflammatory effect of nutrients and higher DII values, which indicate an increased intake of nutrients with pro-inflammatory effects, relate to an increased risk of metabolic and cardiovascular diseases and we here assessed whether they reflect biologically relevant plasmatic variations of inflammatory proteins. METHODS: In this cross-sectional study, seven days dietary records from 663 subjects in primary prevention for cardiovascular diseases were analyzed to derive the intake of nutrients, foods and to calculate DII. To associate DII with the Normalized Protein eXpression (NPX), an index of abundance, of a targeted panel of 368 inflammatory biomarkers (Olink™) measured in the plasma, we divided the population by the median value of DII (1.60 (0.83-2.30)). RESULTS: 332 subjects with estimated DII over the median value reported a higher intake of saturated fats but lower intakes of poly-unsaturated fats, including omega-3 and omega-6 fats, versus subjects with estimated dietary DII below the median value (N = 331). The NPX of 61 proteins was increased in the plasma of subjects with DII > median vs. subjects with DII < median. By contrast, in the latter group, we underscored only 3 proteins with increased NPX. Only 23, out of these 64 proteins, accurately identified subjects with DII > median (Area Under the Curve = 0.601 (0.519-0.668), p = 0.035). CONCLUSION: This large-scale proteomic study supports that higher DII reflects changes in the plasmatic abundance of inflammatory proteins. Larger studies are warranted to validate.

Draft genome sequences of multiple bacterial strains isolated from human feces.

Bacterial isolation is necessary for functional and mechanistic analyses, and the increased human microbiome diversity revealed by metagenomic sequencing is expanding the relevant cultivation targets. Here, we report 46 draft genome sequences of bacterial isolates obtained from fecal samples of healthy adults in Trento and Milan (Italy), including strains from seven taxonomically uncharacterized species.

Favorable subgingival plaque microbiome shifts are associated with clinical treatment for peri-implant diseases.

We performed a longitudinal shotgun metagenomic investigation of the plaque microbiome associated with peri-implant diseases in a cohort of 91 subjects with 320 quality-controlled metagenomes. Through recently improved taxonomic profiling methods, we identified the most discriminative species between healthy and diseased subjects at baseline, evaluated their change over time, and provided evidence that clinical treatment had a positive effect on plaque microbiome composition in patients affected by mucositis and peri-implantitis.

Paternal and induced gut microbiota seeding complement mother-to-infant transmission.

Microbial colonization of the neonatal gut involves maternal seeding, which is partially disrupted in cesarean-born infants and after intrapartum antibiotic prophylaxis. However, other physically close individuals could complement such seeding. To assess the role of both parents and of induced seeding, we analyzed two longitudinal metagenomic datasets (health and early life microbiota [HELMi]: N = 74 infants, 398 samples, and SECFLOR: N = 7 infants, 35 samples) with cesarean-born infants who received maternal fecal microbiota transplantation (FMT). We found that the father constitutes a stable source of strains for the infant independently of the delivery mode, with the cumulative contribution becoming comparable to that of the mother after 1 year. Maternal FMT increased mother-infant strain sharing in cesarean-born infants, raising the average bacterial empirical growth rate while reducing pathogen colonization. Overall, our results indicate that maternal seeding is partly complemented by that of the father and support the potential of induced seeding to restore potential deviations in this process.

Neuroblastoma is associated with alterations in gut microbiome composition subsequent to maternal microbial seeding.

BACKGROUND: Neuroblastoma is the most frequent extracranial solid tumour in children, accounting for ∼15% of deaths due to cancer in childhood. The most common clinical presentation are abdominal tumours. An altered gut microbiome composition has been linked to multiple cancer types, and reported in murine models of neuroblastoma. Whether children with neuroblastoma display alterations in gut microbiome composition remains unexplored. METHODS: We assessed gut microbiome composition by shotgun metagenomic profiling in an observational cross-sectional study on 288 individuals, consisting of patients with a diagnosis of neuroblastoma at disease onset (N = 63), healthy controls matching the patients on the main covariates of microbiome composition (N = 94), healthy siblings of the patients (N = 13), mothers of patients (N = 59), and mothers of the controls (N = 59). We examined taxonomic and functional microbiome composition and mother-infant strain transmission patterns. FINDINGS: Patients with neuroblastoma displayed alterations in gut microbiome composition characterised by reduced microbiome richness, decreased relative abundances of 18 species (including Phocaeicola dorei and Bifidobacterium bifidum), enriched protein fermentation and reduced carbohydrate fermentation potential. Using machine learning, we could successfully discriminate patients from controls (AUC = 82%). Healthy siblings did not display such alterations but resembled the healthy control group. No significant differences in maternal microbiome composition nor mother-to-offspring transmission were detected. INTERPRETATION: Patients with neuroblastoma display alterations in taxonomic and functional gut microbiome composition, which cannot be traced to differential maternal seeding. Follow-up research should include investigating potential causal links. FUNDING: Italian Ministry of Health Ricerca Corrente and Ricerca Finalizzata 5 per mille (to MPonzoni); Fondazione Italiana Neuroblastoma (to MPonzoni); European Research Council (ERC-StG project MetaPG-716575 and ERC-CoG microTOUCH-101045015 to NS); the European H2020 program ONCOBIOME-825410 project (to NS); the National Cancer Institute of the National Institutes of Health 1U01CA230551 (to NS); the Premio Internazionale Lombardia e Ricerca 2019 (to NS); the MIUR Progetti di Ricerca di Rilevante Interesse Nazionale (PRIN) Bando 2017 Grant 2017J3E2W2 (to NS); EMBO ALTF 593-2020 and Knowledge Generation Project from the Spanish Ministry of Science and Innovation (PID2022-139328OA-I00) (to MV-C).

Inter-facility characterization of bacteria in seafood processing plants: Exploring potential reservoirs of spoilage organisms and the resistome.

A study was conducted in fish processing facilities to investigate the microbial composition, microbial metabolic potential, and distribution of antibiotic resistance genes. Whole metagenomic sequencing was used to analyze microbial communities from different processing rooms, operators and fish products. Taxonomic analyses identified the genera Pseudomonas and Psychrobacter as the most prevalent bacteria. A Principal Component Analysis revealed a distinct separation between fish product and environmental samples, as well as differences between fish product samples from companies processing either Gadidae or Salmonidae fish. Some particular bacterial genera and species were associated with specific processing rooms and operators. Metabolic analysis of metagenome assembled genomes demonstrated variations in microbiota metabolic profiles of microbiota across rooms and fish products. The study also examined the presence of antibiotic-resistance genes in fish processing environments, contributing to the understanding of microbial dynamics, metabolic potential, and implications for fish spoilage.

Discovering and exploring the hidden diversity of human gut viruses using highly enriched virome samples.

Viruses are an abundant and crucial component of the human microbiome, but accurately discovering them via metagenomics is still challenging. Currently, the available viral reference genomes poorly represent the diversity in microbiome samples, and expanding such a set of viral references is difficult. As a result, many viruses are still undetectable through metagenomics even when considering the power of de novo metagenomic assembly and binning, as viruses lack universal markers. Here, we describe a novel approach to catalog new viral members of the human gut microbiome and show how the resulting resource improves metagenomic analyses. We retrieved >3,000 viral-like particles (VLP) enriched metagenomic samples (viromes), evaluated the efficiency of the enrichment in each sample to leverage the viromes of highest purity, and applied multiple analysis steps involving assembly and comparison with hundreds of thousands of metagenome-assembled genomes to discover new viral genomes. We reported over 162,000 viral sequences passing quality control from thousands of gut metagenomes and viromes. The great majority of the retrieved viral sequences (~94.4%) were of unknown origin, most had a CRISPR spacer matching host bacteria, and four of them could be detected in >50% of a set of 18,756 gut metagenomes we surveyed. We included the obtained collection of sequences in a new MetaPhlAn 4.1 release, which can quantify reads within a metagenome matching the known and newly uncovered viral diversity. Additionally, we released the viral database for further virome and metagenomic studies of the human microbiome.