Metagenomic Profiling Research Articles

Altered fecal microbiome and metabolome profiles in rat models of short bowel syndrome.

Short bowel syndrome (SBS) is featured by impaired nutrients and fluids absorption due to massive small intestine resection. Gut dysbiosis has been implicated in SBS, this study aimed to characterize the metagenomic and metabolomic profiles of SBS and identify potential therapeutic targets. Fecal samples from SBS and Sham rats (n = 8 per group) were collected for high-throughput metagenomic sequencing. Fecal metabolomics was measured by untargeted liquid chromatography-mass spectrometry. We found that the species-level α-diversity significantly decreased in SBS rats, accompanied by altered microbiome compositions. The beneficial anaerobes from Firmicutes and Bacteroidetes were depleted while microorganisms from Lactobacillus, Escherichia, Enterococcus, and Streptococcus were enriched in faces from SBS rats. LEfSe analysis identified 17 microbial species and 38 KEGG modules that were remarkably distinct between SBS and Sham rats. In total, 1,577 metabolites with known chemical identity were detected from all samples, among them, 276 metabolites were down-regulated and 224 metabolites were up-regulated in SBS group. The typical signatures of SBS fecal metabolome comprised reduced short-chain fatty acids and products of amino acid metabolism (indole derivatives and p-cresol), as well as altered bile acid spectrum. We revealed 215 robust associations between representative differentially abundant microbial species and metabolites, the species with the same changing trend tended to have a similar correlation with some certain metabolites. The fecal microbiome and metabolome significantly altered in SBS. Our findings may lay the foundation for developing new strategies to facilitate intestinal adaptation in SBS patients.

Impaired flux of bile acids from the liver to the gut reveals microbiome-immune interactions associated with liver damage

Currently, there is evidence that alteration in the gut ecosystem contributes to the development of liver diseases, however, the complex mechanisms involved are still unclear. We induced cholestasis in mice by bile duct ligation (BDL), mirroring the phenotype of a bile duct obstruction, to understand how gut microbiota alterations caused by an impaired flow of bile acid to the gut contribute to the pathogenesis and progression of liver disease. We performed longitudinal stool, heart, and liver sampling using mice receiving BDL and controls receiving sham operation (ShamOP). Shotgun metagenomics profiling using fecal samples taken before and on day 1, day 3, and day 7 after surgery was performed, and the cytokines and clinical chemistry profiles from heart blood, as well as the liver bile acids profile, were measured. The BDL surgery reshaped the microbiome of mice, resulting in highly distinct characteristics compared to the ShamOP. Our analysis of the microbiome pathways and ECs revealed that BDL reduces the production of hepatoprotective compounds in the gut, such as biotin, spermidine, arginine, and ornithine, which were negatively associated with inflammatory cytokines (IL-6, IL-23, MCP-1). The reduction of the functional potential of the gut microbiota in producing those hepatoprotective compounds is associated with the decrease of beneficial bacteria species from Anaerotruncus, Blautia, Eubacterium, and Lachnoclostridium genera, as well as the increase of disease-associated bacteria e.g., Escherichia coli and Entercoccus faecalis. Our findings advances our knowledge of the gut microbiome-bile acids-liver triangle, which may serve as a potential therapeutic strategy for liver diseases.

Alteration of the fecal microbiome in patients with cholecystectomy: potential relationship with postcholecystectomy diarrhea - before and after study.

Bile acid (BA) is a crucial determinant of the gut microbiome, and cholecystectomy can alter the physiology of BA. Physiological changes in BA resulting from cholecystectomy can also influence the gut microbiome. We aimed to identify the specific taxa associated with perioperative symptoms, including postcholecystectomy diarrhea (PCD), and to evaluate the effect of cholecystectomy on the microbiome by investigating the fecal microbiome of patients with gallstones. We analyzed the fecal samples of 39 patients with gallstones (GS group) and 26 healthy controls (HC group) to evaluate their gut microbiome. We also collected fecal samples from GS group 3 months postcholecystectomy. Symptoms of patients were evaluated before and after cholecystectomy. Further, 16S ribosomal RNA amplification and sequencing were performed to determine the metagenomic profile of fecal samples. The microbiome composition of GS differed from that of HC; however, the alpha diversity was not different. No significant microbiome alterations were observed before and after cholecystectomy. Moreover, GS group showed a significantly lower Firmicutes to Bacteroidetes ratio before and after cholecystectomy than the HC group (6.2, P<0.05). The inter-microbiome relationship was lower in GS than in HC and tended to recover 3 months after surgery. Furthermore, ~28.1% (n=9) of patients developed PCD after surgery. The most prominent species among PCD (+) patients was Phocaeicola vulgatus. Compared with the preoperative state, Sutterellaceae, Phocaeicola, and Bacteroidals were the most dominant taxa among PCD (+) patients. GS group showed a different microbiome from that of HC; however, their microbiomes were not different 3 months after cholecystectomy. Our data revealed taxa-associated PCD, highlighting the possibility of symptom relief by restoring the gut microbiome.

Metagenomic profiles of planktonic bacteria and resistome along a salinity gradient in the Pearl River Estuary, South China

Estuarine ecosystems undergo pronounced and intricate changes due to the mixing of freshwater and saltwater. Additionally, urbanization and population growth in estuarine regions result in shifts in the planktonic bacterial community and the accumulation of antibiotic resistance genes (ARGs). The dynamic changes in bacterial communities, environmental factors, and carriage of ARGs from freshwater to seawater, as well as the complex interrelationships among these factors, have yet to be fully elucidated. Here, we conducted a comprehensive study based on metagenomic sequencing and full-length 16S rRNA sequencing, covering the entire Pearl River Estuary (PRE) in Guangdong, China. The abundance and distribution of the bacterial community, ARGs, mobile genetic elements (MGEs), and bacterial virulence factors (VFs) were analyzed on a site-by-site basis through sampling along the salinity gradient in PRE, from upstream to downstream. The structure of the planktonic bacterial community undergoes continuous changes in response to variations in estuarine salinity, with the phyla Proteobacteria and Cyanobacteria being dominant bacterial throughout the entire region. The diversity and abundance of ARGs and MGEs gradually decreased with the direction of water flow. A large number of ARGs were carried by potentially pathogenic bacteria, especially in Alpha-proteobacteria and Beta-proteobacteria. Multi-drug resistance genes have the highest abundance and subtypes in PRE. In addition, ARGs are more linked to some MGEs than to specific bacterial taxa and disseminate mainly by HGT and not by vertical transfer in the bacterial communities. Various environmental factors, such as salinity and nutrient concentrations, have a significantly impact on the community structure and distribution of bacteria. In conclusion, our results represent a valuable resource for further investigating the intricate interplay between environmental factors and anthropogenic disturbances on bacterial community dynamics. Moreover, they contribute to a better understanding of the relative impact of these factors on the dissemination of ARGs.

Soil polluted with nano ZnO reveals unstable bacterial communities and decoupling of taxonomic and functional diversities

Due to relentless production and disposal of nano zinc oxide (nZnO), it has become critical to comprehend the serious risks large-scale accumulation of nZnO pose to bacterial communities in soil. The primary objective was to evaluate the changes in bacterial community structure and associated functional pathways through predictive metagenomic profiling and subsequent validation through Quantitative Realtime PCR in soil spiked with nZnO (0, 50, 200, 500 and 1000 mg Zn kg−1) and similar levels of bulk ZnO (bZnO). The results revealed that soil microbial biomass-C, -N, -P, soil respiration and enzyme activities decreased markedly at higher ZnO levels. The alpha diversity decreased with increasing ZnO level, with more impact under nZnO, while beta diversity analyses indicated a distinct dose- dependent separation of bacterial communities. The dominant taxa including Proteobacteria, Bacterioidetes, Acidobacteria and Planctomycetes significantly increased in abundance, while Firmicutes, Actinobacteria and Chloroflexi decreased in abundance with elevated nZnO and bZnO levels. Redundancy analysis indicated that changes in bacterial community structure instilled a greater dose- rather than size- specific response on key microbial parameters. Predicted key functions did not show a dose- specific response, and at 1000 mg Zn kg−1, methane metabolism as well as starch and sucrose metabolism were attenuated, while functions involving two component systems and bacterial secretion systems were enhanced under bZnO indicating better stress avoidance mechanism than under nZnO. Realtime PCR and microbial endpoint assays confirmed the metagenome derived taxonomic and functional data, respectively. Taxa and functions that varied substantially under stress were established as bioindicators to predict nZnO toxicity in soils. Taxon-function decoupling indicated that the soil bacterial communities deployed adaptive mechanisms under high ZnO, with lesser buffering capacity and resilience of communities under nZnO.

Administration of Bifidobacterium animalis subsp. lactis strain BB-12® in healthy children: characterization, functional composition, and metabolism of the gut microbiome.

The consumption of probiotics may influence children's gut microbiome and metabolome, which may reflect shifts in gut microbial diversity composition and metabolism. These potential changes might have a beneficial impact on health. However, there is a lack of evidence investigating the effect of probiotics on the gut microbiome and metabolome of children. We aimed to examine the potential impact of a two (Streptococcus thermophilus and Lactobacillus delbrueckii; S2) vs. three (S2 + Bifidobacterium animalis subsp. lactis strain BB-12) strain-supplemented yogurt. Included in this study were 59 participants, aged one to five years old, recruited to phase I of a double-blinded, randomized controlled trial. Fecal samples were collected at baseline, after the intervention, and at twenty days post-intervention discontinuation, and untargeted metabolomics and shotgun metagenomics were performed. Shotgun metagenomics and metabolomic analyses showed no global changes in either intervention group's gut microbiome alpha or beta diversity indices, except for a lower microbial diversity in the S2 + BB12 group at Day 30. The relative abundance of the two and three intervention bacteria increased in the S2 and S2 + BB12 groups, respectively, from Day 0 to Day 10. In the S2 + BB12 group, the abundance of several fecal metabolites increased at Day 10, including alanine, glycine, lysine, phenylalanine, serine, and valine. These fecal metabolite changes did not occur in the S2 group. In conclusion, there were were no significant differences in the global metagenomic or metabolomic profiles between healthy children receiving two (S2) vs. three (S2 + BB12) probiotic strains for 10 days. Nevertheless, we observed a significant increase (Day 0 to Day 10) in the relative abundance of the two and three probiotics administered in the S2 and S2 + BB12 groups, respectively, indicating the intervention had a measurable impact on the bacteria of interest in the gut microbiome. Future research using longer probiotic intervention durations and in children at risk for gastrointestinal disorders may elucidate if functional metabolite changes confer a protective gastrointestinal effect.

Pain sensation and gut microbiota profiles in older adults with heart failure.

Patients with heart failure (HF) experience severe pain and may have altered pain sensation; however, the underlying mechanisms of these symptoms are not yet fully understood. Identifying pain sensation and genomic biomarkers of pain in older adults with HF is a critical step toward developing personalized interventions to improve pain management and outcomes. This study aimed to investigate the differences in pain sensation, gut microbiota, self-reported pain, and symptoms in older adults with and without HF. Twenty older adults with HF and age-matched healthy controls (HCs) were recruited in the Northeastern United States. Quantitative sensory testing and conditioned pain modulation were performed on the nondominant upper arm to detect the mechanical, thermal, and pressure pain thresholds and pain modulations. Stool samples were collected, and the 16S rRNA V4 gene region of stool samples was sequenced and processed using the Mothur 1.42.3 pipeline. Self-reported pain and symptoms were measured by the Brief Pain Inventory and the NIH Patient-reported Outcomes Measurement Information System. The associations between pain sensation, gut microbiota α-diversity indices, and pain and symptoms were explored using the Spearman correlations. The HF and HC subjects' mean ages were 73.50 (SD = 8.33) and 67.10 (SD = 7.64), respectively. The HF subjects reported significantly higher pain intensity and interference, sleep disturbance, fatigue, anxiety, and depression than the HCs. The HF subjects also had a significantly lower level of physical function and participation in social roles and activities. Compared with the HCs, the HF subjects had significantly altered conditioned pain modulation heat effect and gut microbiota compositions and predicted metabolic functions. The Statistical Analysis Of Metagenomic Profiles indicated that the HF subjects had a significantly decreased cardiac muscle contraction pathway compared with the HCs. The correlation analysis showed that the quantitative sensory testing profiles and gut microbiota diversity index were significantly associated with pain and symptoms in older adults with HF. Older adults with HF had more severe self-reported pain and symptoms, altered pain sensation, and different gut microbiota composition and function compared with age-matched HCs. Pain sensation and gut microbiota may contribute to pain and symptoms in older adults with HF and could serve as biomarkers of pain and symptoms of HF. Further research with a larger sample size is warranted to confirm these findings.

MetaPhlAn 4 profiling of unknown species-level genome bins improves the characterization of diet-associated microbiome changes in mice

Mouse models are key tools for investigating host-microbiome interactions. However, shotgun metagenomics can only profile a limited fraction of the mouse gut microbiome. Here, we employ a metagenomic profiling method, MetaPhlAn 4, which exploits a large catalog of metagenome-assembled genomes (including 22,718 metagenome-assembled genomes from mice) to improve the profiling of the mouse gut microbiome. We combine 622 samples from eight public datasets and an additional cohort of 97 mouse microbiomes, and we assess the potential of MetaPhlAn 4 to better identify diet-related changes in the host microbiome using a meta-analysis approach. We find multiple, strong, and reproducible diet-related microbial biomarkers, largely increasing those identifiable by other available methods relying only on reference information. The strongest drivers of the diet-induced changes are uncharacterized and previously undetected taxa, confirming the importance of adopting metagenomic methods integrating metagenomic assemblies for comprehensive profiling.

Changes of gut microbiota reflect the severity of major depressive disorder: a cross sectional study

Disturbed gut microbiota is a potential factor in the pathogenesis of major depressive disorder (MDD), yet whether gut microbiota dysbiosis is associated with the severity of MDD remains unclear. Here, we performed shotgun metagenomic profiling of cross-sectional stool samples from MDD (n = 138) and healthy controls (n = 155). The patients with MDD were divided into three groups according to Hamilton Depression Rating Scale 17 (HAMD-17), including mild (n = 24), moderate (n = 72) and severe (n = 42) individuals, respectively. We found that microbial diversity was closely related to the severity of MDD. Compared to HCs, the abundance of Bacteroides was significantly increased in both moderate and severe MDD, while Ruminococcus and Eubacterium depleted mainly in severe group. In addition, we identified 99 bacteria species specific to severity of depression. Furthermore, a panel of microbiota marker comprising of 37 bacteria species enabled to effectively distinguish MDD patients with different severity. Together, we identified different perturbation patterns of gut microbiota in mild-to-severe depression, and identified potential diagnostic and therapeutic targets.

Exploring the Bacterial Community in Aged Fecal Sources from Dairy Cows: Impacts on Fecal Source Tracking.

(1) Background: This paper discusses the impact of agricultural activities on stream health, particularly in relation to dairy cow fecal pollution. The study explores the fecal microbiome of cattle and the potential ecological implications of aging fecal pollution on waterways. (2) Methods: The study examines changes in the bacterial community available for mobilization from in-situ decomposing cowpats and the effects of simulated rainfall. The microbiome of individual cowpats was monitored over 5.5 months. We used 16S rRNA metagenomics and machine learning software, FEAST (Fast Expectation-mAximization for microbial Source Tracking), for bacterial and fecal source assignments. (3) Results: The phyla Bacillota and Bacteroidota are dominant in the fecal microbiota of fresh cow feces but shift to Pseudomonodota, Actinomycetota, and environmental Bacteroidota in aged cowpats. Potential impacts of these bacterial community shifts on inputs to local agricultural streams are discussed in relation to water quality monitoring and aging sources of fecal contamination. We identified taxon orders that are potential indicators of fresh cattle sources (Oscillospirales and Bacteroidales) and aged sources (Peptostreptococcales-Tissierellales) in water bodies. (4) The paper highlights that bacterial metagenomic profiling can inform our understanding of the ecology of microbial communities in aquatic environments and the potential impacts of agricultural activities on ecosystem health.

Suppression of the gut microbiota-bile acid-FGF19 axis in patients with atrial fibrillation.

This study aimed to investigate the role of the gut microbiota (GM)-bile acid (BA)-fibroblast growth factor (FGF) 19 axis in patients with atrial fibrillation (AF). Gut bacterial metabolisms of BAs were determined in an AF metagenomic dataset. The composition of faecal BAs pools was characterized by targeted metabolomics in an independent AF cross-sectional cohort. Circulating levels of FGF19 were measured by ELISA. In vitro cell experiments were conducted to validate the regulatory role of FGF19 in atrial cardiomyocytes stimulated with palmitic acid. First, metagenomic profiling revealed that gut microbial biotransformation from primary to secondary BAs was dysregulated in AF patients. Second, the proportion of secondary BAs decreased in the faeces of patients with AF. Also, eight BAs were identified as AF-associated BAs, including seven AF-enriched BAs (ursodeoxycholic acid, chenodeoxycholic acid, etc.), and AF-decreased dehydrolithocholic acid. Third, reduced levels of circulating FGF19 were observed in patients with AF. Subsequently, FGF19 was found to protect against palmitic acid-induced lipid accumulation and dysregulated signalling in atrial cardiomyocytes, including attenuated phosphorylation of YAP and Ca2+ /calmodulin-dependent protein kinases II and secretion of interleukin-1β, mediated via peroxisome proliferator-activated receptor α. Our data found decreased levels of secondary BAs and circulating FGF19, resulting in the impaired protective function of FGF19 against lipid accumulation in atrial cardiomyocytes.

Gut microbiome responds compositionally and functionally to the seasonal diet variations in wild gibbons

Wild animals may encounter multiple challenges especially food shortage and altered diet composition in their suboptimal ranges. Yet, how the gut microbiome responds to dietary changes remains poorly understood. Prior studies on wild animal microbiomes have typically leaned upon relatively coarse dietary records and individually unresolved fecal samples. Here, we conducted a longitudinal study integrating 514 time-series individually recognized fecal samples with parallel fine-grained dietary data from two Skywalker hoolock gibbon (Hoolock tianxing) groups populating high-altitude mountainous forests in western Yunnan Province, China. 16S rRNA gene amplicon sequencing showed a remarkable seasonal fluctuation in the gibbons’ gut microbial community structure both across individuals and between the social groups, especially driven by the relative abundances of Lanchnospiraceae and Oscillospiraceae associated with fluctuating consumption of leaf. Metagenomic functional profiling revealed that diverse metabolisms associated with cellulose degradation and short-chain fatty acids (SCFAs) production were enriched in the high-leaf periods possibly to compensate for energy intake. Genome-resolved metagenomics further enabled the resolving metabolic capacities associated with carbohydrate breakdown among community members which exhibited a high degree of functional redundancy. Our results highlight a taxonomically and functionally sensitive gut microbiome actively responding to the seasonally shifting diet, facilitating the survival and reproduction of the endangered gibbon species in their suboptimal habitats.

Metagenomic profile of the bacterial communities associated with Ixodes granulatus (Acari: Ixodidae): a potential vector of tick-borne diseases.

Ixodes granulatus Supino, 1897 (Acari: Ixodida) is one of Malaysia's most common hard ticks and is a potential vector for tick-borne diseases (TBDs). Despite its great public health importance, research on I. granulatus microbial communities remains largely unexplored. Therefore, this study aimed to investigate the bacterial communities of on-host I. granulatus collected from three different recreational areas on the East Coast of Peninsular Malaysia using high throughput Next Generation Sequencing (NGS). A total of 9 females on-host I. granulatus were subjected to metabarcoding analysis targeting V3-V4 regions of 16S ribosomal RNA (rRNA) using the Illumina MiSeq platform. This study identified 15 bacterial phyla corresponding to 19 classes, 54 orders, and 90 families from 435 amplicon sequence variants (ASVs), revealing a diverse bacterial community profile. Together with 130 genera assigned, local I. granulatus harbored 4 genera of pathogens, i.e., Rickettsia da Rocha Lima, 1916 (Rickettsiales: Rickettsiaceae) (58.6%), Borrelia Swellengrebel 1907 (Spirochaetales: Borreliaceae) (31.6%), Borreliella Adeolu and Gupta 2015 (Spirochaetales: Borreliaceae) (0.6%), and Ehrlichia Cowdria Moshkovski 1947 (Rickettsiales: Ehrlichiaceae) (39.9%). Some endosymbiont bacteria, such as Coxiella (Philip, 1943) (Legionellales: Coxiellaceae), Wolbachia Hertig 1936 (Rickettsiales: Ehrlichiaceae), and Rickettsiella Philip, 1956 (Legionellales: Coxiellaceae), were also detected at very low abundance. Interestingly, this study reported the co-infection of Borrelia and Ehrlichia for the first time, instilling potential health concerns in the context of co-transmission to humans, especially in areas with a high population of I. granulatus. This study successfully characterized the tick microbiome and provided the first baseline data of I. granulatus bacterial communities in Malaysia. These results support the need for way-forward research on tick-associated bacteria using NGS, focusing on medically important species toward TBD prevention.

Metagenomic profiling of antibiotic resistance genes in Red Sea brine pools.

Antibiotic resistance (AR) is an alarming global health concern, causing an annual death rate of more than 35,000 deaths in the US. AR is a natural phenomenon, reported in several pristine environments. In this study, we report AR in pristine Red Sea deep brine pools. Antimicrobial resistance genes (ARGs) were detected for several drug classes with tetracycline and macrolide resistance being the most abundant. As expected, ARGs abundance increased in accordance with the level of human impact with pristine Red Sea samples having the lowest mean ARG level followed by estuary samples, while activated sludge samples showed a significantly higher ARG level. ARG hierarchical clustering grouped drug classes for which resistance was detected in Atlantis II Deep brine pool independent of the rest of the samples. ARG abundance was significantly lower in the Discovery Deep brine pool. A correlation between integrons and ARGs abundance in brine pristine samples could be detected, while insertion sequences and plasmids showed a correlation with ARGs abundance in human-impacted samples not seen in brine pristine samples. This suggests different roles of distinct mobile genetic elements (MGEs) in ARG distribution in pristine versus human-impacted sites. Additionally, we showed the presence of mobile antibiotic resistance genes in the Atlantis II brine pool as evidenced by the co-existence of integrases and plasmid replication proteins on the same contigs harboring predicted multidrug-resistant efflux pumps. This study addresses the role of non-pathogenic environmental bacteria as a silent reservoir for ARGs, and the possible horizontal gene transfer mechanism mediating ARG acquisition.

Microbial Communities of Flor Velums and the Genetic Stability of Flor Yeasts Used for a Long Time for the Industrial Production of Sherry-like Wines

Flor yeast strains represent a specialized group of Saccharomyces cerevisiae yeasts used for the production of sherry-like wines by biological wine aging. We sequenced the genome of the industrial flor yeast strain I-329 from a collection of microorganisms for winemaking “Magarach” and the metagenomes of two flor velums based on this strain and continuously maintained for several decades. The winery uses two processes for the production of sherry-like wine: batch aging and a continuous process similar to the criaderas–solera system. The 18S rRNA gene profiling and sequencing of metagenomes of flor velums revealed the presence of the yeasts Pichia membranifaciens and Malassezia restricta in minor amounts along with the dominant S. cerevisiae I-329 flor yeast. Bacteria Oenococcus oeni and Lentilactobacillus hilgardii together accounted for approximately 20% of the velum microbiota in the case of a batch process, but less than 1% in the velum used in the continuous process. Collection strain I-329 was triploid for all chromosomes except diploid chromosomes I and III, while the copy numbers of all chromosomes were equal in industrial velums. A comparative analysis of the genome of strain I-329 maintained in the collection and metagenomes of industrial velums revealed only several dozens of single nucleotide polymorphisms, which indicates a long-term genetic stability of this flor yeast strain under the harsh conditions of biological wine aging.

The selection of software and database for metagenomics sequence analysis impacts the outcome of microbial profiling and pathogen detection.

Shotgun metagenomic sequencing analysis is widely used for microbial profiling of biological specimens and pathogen detection. However, very little is known about the technical biases caused by the choice of analysis software and databases on the biological specimen. In this study, we evaluated different direct read shotgun metagenomics taxonomic profiling software to characterize the microbial compositions of simulated mice gut microbiome samples and of biological samples collected from wild rodents across multiple taxonomic levels. Using ten of the most widely used metagenomics software and four different databases, we demonstrated that obtaining an accurate species-level microbial profile using the current direct read metagenomics profiling software is still a challenging task. We also showed that the discrepancies in results when different databases and software were used could lead to significant variations in the distinct microbial taxa classified, in the characterizations of the microbial communities, and in the differentially abundant taxa identified. Differences in database contents and read profiling algorithms are the main contributors for these discrepancies. The inclusion of host genomes and of genomes of the interested taxa in the databases is important for increasing the accuracy of profiling. Our analysis also showed that software included in this study differed in their ability to detect the presence of Leptospira, a major zoonotic pathogen of one health importance, especially at the species level resolution. We concluded that using different databases and software combinations can result in confounding biological conclusions in microbial profiling. Our study warrants that software and database selection must be based on the purpose of the study.

Abstract 6224: Exploring the integration of CMS subtyping and other omics in colorectal cancer classification and its reflection in stool miRNome and metagenome for non-invasive precision medicine

Abstract Background: The Consensus Molecular Subtypes (CMS) is a subtyping system used for colorectal cancer (CRC) to facilitate traditional tumor classification and clinical translation. Relying on RNA-seq data, the system classifies patients into four molecular subtypes (CMS 1-4). Each subtype is enriched with several mutations, but no genetic aberrations are peculiar to a single CMS. A more in-depth characterization of each subtype's genomic and epigenomic background by integrating different omics may help in refining this classification, including the missing assignment of a subgroup of tumors. The possible translation of this improved classification to surrogate tissues, such as stool, has never been investigated. Aims: We aim to comprehensively characterize the CMS by the integrative analysis of target genomic sequencing, RNA-Seq, small RNA-Seq, and immune infiltrate profiling data of a cohort of CRC patients. These data will be used to identify integrative CMS-specific signatures and to characterize those tumors not assigned to any CMS. In addition, differences in stool miRNome and metagenomic profiles will be explored to identify potential specific signatures characterizing each subtype. Methods: Tumor tissue and adjacent mucosa were collected from 87 CRC patients and preserved in RNA later. mRNA and other non-coding RNA expression levels were evaluated with ribosomal depleted RNA-seq and small RNA-seq. Tumors were assigned to a CMS subtype using the CMScaller algorithm and genomically characterized with the TruSight Oncology 500 (TSO500) cancer panel. Differential expression analyses were performed using the DESeq2 package for the R software to identify CMS-specific expression signatures. Small RNA-seq and shotgun metagenomic analyses were performed on stool samples collected from the same patients. Preliminary Results: Tumors were assigned to CMS1 (n=9), CMS2 (n=24), CMS3 (n=26), and CMS4 (n=22), except for six samples. Differential expression analyses between paired tumor samples and adjacent mucosa within each CMS revealed 1096 differentially expressed genes in CMS1, 4218 in CMS2, 27 in CMS3 and 190 in CMS4. From the genomic point of view, CMS3 cases showed 384 unique missense variants, while CMS1 included almost all samples with microsatellite instability. Small RNA-seq on the same tissue sample identified 380 dysregulated miRNAs (215 up and 165 downregulated) in the tumor compared to adjacent mucosa. Conclusions: A more in-depth CMS subtyping by integrating different omics analyses could help refine this classification system. Moreover, the possible CMS reflection in stool miRNome and metagenomic could shed new light on the host gut-microbiota interactions and allow a non-invasive classification applicable for a routine personalized clinical management of CRC. Citation Format: Amedeo Gagliardi, Giulia Francesca, Giulio Ferrero, Sonia Tarallo, Giulia Piaggeschi, Antonio Francavilla, Carla Di Battista, Enrico Berrino, Caterina Marchiò, Francesca Cordero, Barbara Pardini, Alessio Naccarati. Exploring the integration of CMS subtyping and other omics in colorectal cancer classification and its reflection in stool miRNome and metagenome for non-invasive precision medicine [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6224.

Abstract 3050: Quality control samples for future population-based microbiome studies

Abstract Introduction: There is a critical need for complex microbiome quality control standards representing population-based samples for microbial community profiling and analysis in large scale epidemiologic studies. Methods: We developed standard quality control samples from five volunteers with different phenotypes, comprising one obese female, one healthy male, one male on a low-carb diet, one infant, and one male with Crohn’s Disease, and evaluated their microbial metagenomic profiles within three laboratories at two different timepoints. To quantify the percentage of microbiome variability explained by donors, laboratory and sequencing run, a distance-based coefficient of determination R2 was estimated using a permutational multivariate analysis of variance. In addition, we calculated the intraclass correlation coefficients (ICC) for the relative abundance of the most abundant species, two alpha diversity metrics (i.e., observed number of species and Shannon index) and the first principal coordinates of three beta diversity matrices (i.e., Bray-Curtis, Jaccard and Aitchison) to estimate the accuracy of fecal microbial profiles between the three different laboratories as well as within the laboratories. Results: The variability introduced by the phenotype of the donors explained 82.7% to 95.3% of the overall variability, which was higher than the variability introduced by the laboratories (1.8% to 3.1%) and the sequencing runs (0.6% to 1.7%) - the residual percent variance explained varied between 2.2% and 12.4%. Observations based on principal coordinates analysis showed that samples clustered by donor and not by laboratory or sequencing runs. The five donor clusters were well separated and very distinct. Based on the comparison of species relative abundances, each donor displayed very different microbial profiles; and the microbial profiles of each donor were comparable between the three different laboratories and the two sequencing runs in each laboratory. The reproducibility within and between the laboratories was good to excellent for most diversity metrics (ICCs higher than 0.97) and species relative abundances (range, ICCs=0.70-0.99); however, the reproducibility of the observed number of species was moderate (ICC=0.64 for the first laboratory, ICC=0.78 for the second laboratory, ICC=0.81 for the third laboratory, and ICC=0.42 between the laboratories). Conclusions: These standard quality control samples can be used as a reference in future population-based epidemiologic studies to pool or meta-analyze microbiome data. Citation Format: Semi Zouiouich, Smriti Karwa, Yunhu Wan, Andrew Chan, Joseph Petrosino, Emma Allen-Vercoe, Rob Knight, Jianxin Shi, Mitchell Gail, Christian Abnet, Emily Vogtmann, Rashmi Sinha. Quality control samples for future population-based microbiome studies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3050.

Effective microbial molecular diagnosis of periodontitis-related pathogen Porphyromonas gingivalis from salivary samples using rgpA gene.

Importance of accurate molecular diagnosis and quantification of particular disease-related pathogenic microorganisms is highlighted as an introductory step to prevent and care for diseases. In this study, we designed a primer/probe set for quantitative real-time polymerase chain reaction (qRT-PCR) targeting rgpA gene, known as the specific virulence factor of periodontitis-related pathogenic bacteria 'Porphyromonas gingivalis', and evaluated its diagnostic efficiency by detecting and quantifying relative bacterial load of P. gingivalis within saliva samples collected from clinical subjects. As a result of qRT-PCR, we confirmed that relative bacterial load of P. gingivalis was detected and quantified within all samples of positive control and periodontitis groups. On the contrary, negative results were confirmed in both negative control and healthy groups. Additionally, as a result of comparison with next-generation sequencing (NGS)-based 16S metagenome profiling data, we confirmed relative bacterial load of P. gingivalis, which was not identified on bacterial classification table created through 16S microbiome analysis, in qRT-PCR results. It showed that an approach to quantifying specific microorganisms by applying qRT-PCR method could solve microbial misclassification issues at species level of an NGS-based 16S microbiome study. In this respect, we suggest that P. gingivalis-specific primer/probe set introduced in present study has efficient applicability in various oral healthcare industries, including periodontitis-related microbial molecular diagnosis field.

Holobiont Urbanism: sampling urban beehives reveals cities’ metagenomes

BackgroundOver half of the world’s population lives in urban areas with, according to the United Nations, nearly 70% expected to live in cities by 2050. Our cities are built by and for humans, but are also complex, adaptive biological systems involving a diversity of other living species. The majority of these species are invisible and constitute the city’s microbiome. Our design decisions for the built environment shape these invisible populations, and as inhabitants we interact with them on a constant basis. A growing body of evidence shows us that human health and well-being are dependent on these interactions. Indeed, multicellular organisms owe meaningful aspects of their development and phenotype to interactions with the microorganisms—bacteria or fungi—with which they live in continual exchange and symbiosis. Therefore, it is meaningful to establish microbial maps of the cities we inhabit. While the processing and sequencing of environmental microbiome samples can be high-throughput, gathering samples is still labor and time intensive, and can require mobilizing large numbers of volunteers to get a snapshot of the microbial landscape of a city.ResultsHere we postulate that honeybees may be effective collaborators in gathering samples of urban microbiota, as they forage daily within a 2-mile radius of their hive. We describe the results of a pilot study conducted with three rooftop beehives in Brooklyn, NY, where we evaluated the potential of various hive materials (honey, debris, hive swabs, bee bodies) to reveal information as to the surrounding metagenomic landscape, and where we conclude that the bee debris are the richest substrate. Based on these results, we profiled 4 additional cities through collected hive debris: Sydney, Melbourne, Venice and Tokyo. We show that each city displays a unique metagenomic profile as seen by honeybees. These profiles yield information relevant to hive health such as known bee symbionts and pathogens. Additionally, we show that this method can be used for human pathogen surveillance, with a proof-of-concept example in which we recover the majority of virulence factor genes for Rickettsia felis, a pathogen known to be responsible for “cat scratch fever”.ConclusionsWe show that this method yields information relevant to hive health and human health, providing a strategy to monitor environmental microbiomes on a city scale. Here we present the results of this study, and discuss them in terms of architectural implications, as well as the potential of this method for epidemic surveillance.