Linear Discriminant Analysis Effect Size Research Articles

Adult Outpatients with Long COVID Infected with SARS-CoV-2 Omicron Variant. Part 1: Oral Microbiota Alterations

BackgroundMany individuals experience long COVID after SARS-CoV-2 infection. As microbiota can influence health, it may change with COVID-19. This study investigated differences in oral microbiota between COVID-19 patients with and without long COVID. MethodsBased on a prospective follow-up investigation, this nested case-control study evaluated the differences in oral microbiota in individuals with and without long COVID (Symptomatic and Asymptomatic groups), which were assessed by 16S rRNA sequencing on tongue coating samples. A predictive model was established using machine learning based on specific differential microbial communities. ResultsOne-hundred-and-eight patients were included (n=54 Symptomatic group). The Symptomatic group had higher Alpha diversity indices (observed_otus, Chao1, Shannon, and Simpson indices), differences in microbial composition (Beta diversity), and microbial dysbiosis with increased diversity and relative abundance of pathogenic bacteria. Marker bacteria (c__Campylobacterota, o__Coriobacteriales, o__Pseudomonadales, and o__Campylobacterales) were associated with long COVID by linear discriminant analysis effect size and receiver operating characteristic curves (AUC 0.821). ConclusionThere were distinct variations in oral microbiota between COVID-19 patients with and without long COVID. Changes in oral microbiota may indicate long COVID.

Wastewater Microbiome Analysis for Population Alcohol Abuse

This study aims to unveil correlations between wastewater microbiota and the catchment-specific population health risk, specifically alcohol abuse, with smoking and obesity as confounding factors. Our study highlights the importance of extracting human-associated microbial communities from wastewater metagenomes by excluding environmental microorganisms, due to their irrelevance to human health. After excluding environmental microbes, we observed strong associations of all three health risk factors, including alcohol abuse, smoking and obesity, with the human gut microbiome in wastewater. The linear discriminant analysis effect size (LEfSe) analysis showed Lactococcus_A, Leuconostoc, Aeromicrobium, Akkermansia, Weissella, Limosilactobacillus, Klebsiella_A, Desulfovibrio and Cloacibacillus as potential microbial biomarkers for alcoholism, after accounting for the confounding effects of smoking and obesity. Functional annotations of microorganisms linked with lower alcoholism rates are primarily related to energy metabolism and intercellular communication. Microorganisms associated with higher alcoholism rates are predominantly involved in immune regulation and cellular DNA architecture. This study highlights the need for a comprehensive exploration of different health risk factors together to identify potential associations between the wastewater microbiome and population lifestyle.

Analysis of blood microbiota in patients with adult-onset Still's disease and sepsis by metagenomic next-generation sequencing.

Aims/Background Adult-onset Still's disease (AOSD) shares similar clinical symptoms with sepsis. Thus, differentiating between AOSD and sepsis presents a great challenge while making diagnosis. This study aimed to analyse the changes in blood microbiota related to AOSD and sepsis using metagenomic next-generation sequencing (mNGS), identify potential biomarkers that distinguish AOSD from sepsis, and explore the diagnostic value of mNGS in differentiation between these two pathological conditions. Methods Clinical data of four AOSD patients and four sepsis patients treated in the Department of Rheumatology and Immunology, The Affiliated Hospital of Xuzhou Medical University between October 2021 and February 2022 were collected. The mNGS diagnostic records of these patients were analysed for microbial correlations in terms of species taxonomic structure and beta diversity by comparing blood microbiota between AOSD and sepsis. The biomarkers with the strongest capability in distinguishing the subgroups were screened using a random forest algorithm. Results There was no statistically significant differences between AOSD patients and sepsis controls in terms of gender and age (p > 0.05). A total of 91 operational taxonomic units (OTUs) were obtained. At the level of phylum, Proteobacteria, Ascomycota and Basidiomycota were present in high abundances in both groups (79.76%, 14.18% and 3.30% vs 54.03%, 32.77% and 5.81%). At the genus level, the abundances of Parainfluenzae, Aspergillus and Ralstonia were the top three highest in the AOSD group (73.88%, 10.92% and 5.48%), while Ralstonia, Aspergillus and Malassezia were ranked as the top three in the sepsis group in term of abundance (48.69%, 27.36% and 5.52%). In beta-diversity analysis, there were advances shown in visual principal coordinates analysis (PCoA) and non-metric multidimensional scaling (NMDS) between the AOSD group and sepsis group (p < 0.05), with little significant differences in the analysis of similarities (Anosim) (p > 0.05). Linear discriminant analysis effect size (LEfSe) showed that Mucoromycota, Saccharomycetes, Moraxellales, Mucorales, Xanthomonadales, Saccharomycetales, Acinetobacter, Stenotrophomonas, Yarrowia, Apophysomyces, Acinetobacter johnson, Yarrowia lipolytica, Apophysomyces variabilis and Stenotrophomonas maltophilia were more enriched in sepsis group (p < 0.05). The top five variables with the strongest capability in distinguishing between AOSD and sepsis were Acinetobacter johnsonii, Apophysomyces variabilis, Propionibacterium acnes, Stenotrophomonas maltophilia and Yarrowia lipolytica. Conclusion The blood microorganisms in AOSD were different from sepsis, and mNGS was potential to distinguish between AOSD and sepsis.

Insights into the Naso-Oropharyngeal Bacterial Composition in Suspected SARS-CoV-2 Cases.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was the causative agent of the coronavirus disease 2019 (COVID-19) pandemic. While research on COVID-19 has mainly focused on its epidemiology, pathogenesis, and treatment, studies on the naso-oropharyngeal microbiota have emerged in the last few years as an overlooked area of research. Here, we analyzed the bacterial community composition of the naso-oropharynx in 50 suspected SARS-CoV-2 cases (43 detected, 7 not detected) from Veraguas province (Panama) distributed across five age categories. Statistical analysis revealed no significant differences (p < 0.05) in bacterial alpha and beta diversities between the groups categorized by SARS-CoV-2 test results, age, or patient status. The genera Corynebacterium, Staphylococcus, Prevotella, Streptococcus, and Tepidiphilus were the most abundant in both detected and not-detected SARS-CoV-2 group. The linear discriminant analysis effect size (LEfSe) for biomarker exploration indicated that Veillonella and Prevotella were enriched in detected and hospitalized patients with SARS-CoV-2 relative to non-detected patients, while Thermoanaerobacterium and Haemophilus were enriched in non-detected patients with SARS-CoV-2. The results also indicated that the genus Corynebacterium was found to decrease in patients with detected SARS-CoV-2 relative to those with non-detected SARS-CoV-2. Understanding the naso-oropharyngeal microbiota provides insights into the diversity, composition, and resilience of the microbial community in patients with SARS-CoV-2.

Humoral immune responses primed by the alteration of gut microbiota were associated with galactose-deficient IgA1 production in IgA nephropathy.

Galactose-deficient IgA1 (GdIgA1) is critical in the formation of immunodeposits in IgA nephropathy (IgAN), whereas the origin of GdIgA1 is unknown. We focused on the immune response to fecal microbiota in patients with IgAN. By running 16S ribosomal RNA gene sequencing, we compared IgAN samples to the control samples from household-matched or non-related individuals. Levels of plasma GdIgA1 and poly-IgA complexes were measured, and candidate microbes that can either incite IgA-directed antibody response or degrade IgA through specific IgA protease activities were identified. The IgAN group showed a distinct composition of fecal microbiota as compared to healthy controls. Particularly, high abundance of Escherichia-Shigella was associated with the disease group based on analyses using receiver operating characteristic (area under curve, 0.837; 95% CI, 0.738-0.914), principle coordinates, and the linear discriminant analysis effect size algorithm (linear discriminant analysis score, 4.56; p < 0.001). Accordingly, the bacterial levels directly correlated with high titers of plasma GdIgA1(r = 0.36, p < 0.001), and patients had higher IgA1 against stx2(2.88 ± 0.46 IU/mL vs. 1.34 ± 0.35 IU/mL, p = 0.03), the main antigen of Escherichia-Shigella. Conversely, the healthy controls showed relatively higher abundance of the commensal bacteria that produce IgA-degrading proteases. Particularly, the abundance of some intestinal bacteria expressing IgA proteases showed an inverse correlation with the levels of plasma GdIgA1 in IgAN. Our data suggest that mucosal IgA production, including those of GdIgA1, is potentially linked to the humoral response to gut Escherichia-Shigella as one of the sources of plasma GdIgA1. Conversely, the IgA protease-producing microbiota in the gut are suppressed in patients with IgAN.

Variations in soil microbial communities in different saline soils under typical Populus spp. vegetation in alpine region of the Qaidam Basin, NW China

Salinization is a severe threat to agriculture and the environment in many areas, and the same in Qaidam Basin, Qinghai Province, Northwestern China. Microorganisms have an important influence on regulating the biochemical cycles of ecosystems; however, systematic research exploring microbial diversity and interactions with saline-soil ecosystems’ environmental variables remains scarce. Thus, 16 S rRNA high-throughput sequencing was performed in this paper to characterize microbial diversity under different levels of salinized soils: non-salinized (NS, 2.25 g/L), moderately salinized (MS, 6.14 g/L) and highly salinized (HS, 9.82 g/L). The alpha diversity results showed that the HS soil was significantly different from the NS and MS soils. An analysis of similarity (ANOSIM) and a principal co-ordinates analysis (PCoA) indicated that NS and MS clustered closely while HS separated from the other two. Significant differences in microbial composition were observed at the taxonomic level. Proteobacteria (42.29–79.23 %) were the most abundant phyla in the studied soils. Gammaproteobacteria (52.49 and 66.61 %) had higher abundance in the MS and HS soils at the class level; Methylophaga and Pseudomonas were the predominant bacteria in the HS soil; and Azotobacter and Methylobacillus were abundant in the MS soil. Most genera belonging to Proteobacteria and Actinobacteria were detected via a linear discriminate analysis (LDA) effect size (LEfSe) analysis, which indicated that microbes with the ability to degrade organic matter and accomplish nutrient cycling can be well-adapted to salt conditions. Further analyses (redundancy analysis and Mantel test) showed that the microbial communities were mainly related to the soil salinity, electrical conductivity (EC1:5), total phosphorus (TP) and ammonia nitrogen (NH4+-N). Overall, the findings of the study can provide insights for better understanding the dominant indigenous microbes and their roles in biochemical cycles in different saline soils in the Qaidam Basin, Qinghai Province, China. The researches related to microbial community under typical poplar species should further clarify the mechanism of plant-microbial interaction and benefit for microbial utilization in salt soil remediation.

Multivariate Analysis and Correlation Study Shows the Impact of Anthropometric and Demographic Variables on Gut Microbiota in Obese Egyptian Children.

Deciphering the gut microbiome's link to obesity is crucial. Our study characterized the gut microbial community in Egyptian children and investigated the effect of covariates on the gut microbiome, body mass index (BMI), geographical location, gender, and age. We used 16S rRNA sequencing to characterize the gut microbial communities of 49 children. We then evaluated these communities for diversity, potential biomarkers, and functional capacity. Alpha diversity of the non-obese group was higher than that of the obese group (Chao1, P = 0.006 and observed species, P = 0.003). Beta diversity analysis revealed significant variations in the gut microbiome between the two geographical locations, Cairo and Ismailia (unweighted UniFrac, P = 0.03) and between obesity statuses, obese and non-obese (weighted UniFrac, P = 0.034; unweighted UniFrac, P = 0.015). We observed a significantly higher Firmicutes/Bacteroidetes ratio in obese males than in non-obese males (P = 0.004). Interestingly, this difference was not seen in females (P = 0.77). Multivariable association with linear models (MaAsLin2) identified 8 microbial features associated with obesity, 12 associated with non-obesity, and found 29 and 13 features specific to Cairo and Ismailia patients, respectively. It has also shown one microbial feature associated with patients under five years old. MaAsLin2, however, failed to recognize any association between gender and the gut microbiome. Moreover, it could find the most predominant features in groups 2-9 but not in group 1. Another method used in the analysis is the Linear discriminant analysis Effect Size (LEfSe) approach, which effectively identified 19 biomarkers linked to obesity, 9 linked non-obesity, 20 linked to patients residing in Cairo, 14 linked to patients in Ismailia, one linked to males, and 12 linked to females. LEfSe could not, however, detect any prevalent bacteria among children younger or older than five. Future studies should take advantage of such correlations, specifically BMI, to determine the interventions needed for obesity management.

Alteration of gut microbiota in Henoch-Schönlein purpura children with gastrointestinal involvement.

The compositional and structural changes of gut microbiota were closely related to the status of Henoch-Schönlein purpura (HSP). To investigate if clinical indicators and gut microbiota differ between HSP patients with or without gastrointestinal (GI) involvement and to explore the alterations of fecal microbiota in HSP children with and without GI symptoms. A total of 22 children with HSP were enrolled in the study. Fecal microbiota composition was analyzed by 16S rRNA sequencing. Clinical indicators, fecal microbial diversity, and compositions were compared between the two groups. Respectively, 9 patients with GI involvement (HSP-A) and 13 patients without GI involvement (HSP-N) were enrolled. Prealbumin (PA) and the ratio of immunoglobulin A (IgA) / complement (C)3 were significantly decreased in the HSP-A group and an elevated D-dimer was found in the HSP-N group. The relative abundances of Blautia, Lachnospira, and Haemophilus were significantly higher in the HSP-A group compared to HSP-N. Lower levels of unidentified Prevotellaceae, Parabacteroides, and Romboutsia were found in HSP-A patients. The linear discriminant analysis effect size (LEfSe) showed that the biomarkers for the HSP-A group included Blautia, Anaerostipes, Veillonella, Lachnospira, and Haemophilus. For the HSP-N group, unidentified Prevotellaceae, Intestinibacter, Romboutsia, and Akkermansia were the prominent biomarkers at the genus level. Additionally, the ratio of IgA/C3 exhibited a negative correlation with the genus Blautia. Meanwhile, PA showed negatively correlation with Veillonella. These results provide a broader understanding for future microbial-based therapies to decrease the development of GI involvement and improve the clinical outcome of HSP in children.

P-327 A multicenter retrospective study of the investigation of detailed immunological inflammatory grading for chronic endometritis and their correlation with the endometrial microbiome

Abstract Study question There exists refractory chronic endometritis which does not respond to antibiotic treatment. This study aims to elucidate its pathogenesis and develop detection methods. Summary answer Through treatment intervention for chronic endometritis (CE), the inflammatory grade decreased overall and the bacteria most associated with endometritis were Lactobacillus iners. What is known already CE and endometrial dysbiosis have been reported to be associated with recurrent pregnancy loss (RPL) and recurrent implantation failure (RIF), but there is insufficient data confirming the interrelation between them. Moreover, the diagnosis of CE typically involves single immunohistochemical staining with CD138, but the diagnostic criteria vary across reports (e.g., McQueen’s method, Liu’s method, etc.) and moreover, use of this classical inflammatory assessment methods raises concerns about their sufficiency in evaluating the pathogenesis of endometritis in cases of RPL and RIF. Study design, size, duration A retrospective analysis was conducted on 206 samples of endometrial specimens collected from infertile patients at seven participating assisted reproductive healthcare facilities from 2021 to 2023. Among these, 73 samples (from 48 cases) had undergone both histological examination and simultaneous endometrial microbiome testing, and data on pregnancy outcomes (including implantation success and ongoing pregnancy rate) were collected until December 2023 for these cases. Participants/materials, setting, methods The endometrial specimens from cases with RIF or RPL were obtained through intrauterine aspiration in luteal phase. Immunohistochemical staining using CD138, CD56, and CD8 antibodies was performed. A composite grading for endometritis, based on histological findings and immunohistochemistry intensity, was established (INF grading; grade 0 to 5). Furthermore, a portion of the specimens underwent microbiome analysis using next-generation sequencing targeting the 16SrRNA, exploring correlations between bacterial taxa, abundance, histological findings, and pregnancy outcomes. Main results and the role of chance Among analyzed 48 cases, 11 cases underwent repeated endometrial microbiome analysis post-treatment again, while 7 cases had additional testing without improvement in chronic endometritis (CE) or endometrial dysbiosis. The McQueen’s method diagnosed 27 cases with CE, while the Liu method identified 4 cases. According to our INF grading, 11 cases were classified as endometritis grade 3 or above. Successful embryo implantation was achieved in 18 cases (37.5%), with ongoing pregnancy in 13 cases (27.1%). CE treatment involved broad-spectrum oral antibiotics, mainly doxycycline and metronidazole, resulting in improvement to grade 2 or below in 9 out of 11 cases with INF grade 3 or above. However, clear associations between pregnancy outcomes and INF grades were not apparent, with the most significant correlation found in CE diagnosis using Liu’s method. Analyzing biomarkers for CE through LEfSe (Linear discriminant analysis effect size), both McQueen’s method and INF grading 2 or above were associated with the intrauterine presence of Lactobacillus iners. Estimating endometrial inflammation based on intrauterine Lactobacillus iners presence yielded an AUC of 0.733 for McQueen’s CE and 0.723 for INF grade 2 or above. Limitations, reasons for caution This study is a retrospective analysis, and the treatment protocols and intervention criteria for chronic endometritis vary among different facilities. The number of cases is also limited, and it is desirable to conduct a unified prospective multicenter cohort study with consistent protocols. Wider implications of the findings The combination of the endometrial microbiome testing and detailed inflammatory grading suggests the potential for establishing appropriate treatment intervention strategies and predicting the success rate of infertile treatment. Since Lactobacillus iners tends to colonize extensively in the vaginal environment of East Asian women, it is necessary to explore region-specific measures. Trial registration number not appicable

Exploring the effects of Saorilao-4 on the gut microbiota of pulmonary fibrosis model rats based on 16S rRNA sequencing.

Pulmonary fibrosis (PF) is a progressive and incurable lung disease for which treatment options are limited. Here, we aimed to conduct an exploratory study on the effects of the Mongolian medicine Saorilao-4 (SRL) on the gut microbiota structure, species abundance, and diversity of a rat PF model as well as the mechanisms underlying such effects. Rat fecal samples were analyzed using 16S rRNA sequencing technology. Bioinformatic and correlation analyses were performed on microbiota data to determine significant associations. SRL substantially attenuated the adverse effects exerted by PF on the structure and diversity of gut microbiota while regulating its alpha and beta diversities. Linear discriminant analysis effect size enabled the identification of 62 differentially abundant microbial taxa. Gut microbiota abundance analysis revealed that SRL significantly increased the relative abundance of bacterial phyla such as Firmicutes and Bacteroidetes. Moreover, SRL increased the proportion of beneficial bacteria, such as Lactobacillus and Bifidobacteriales, decreased the proportion of pathogenic bacteria, such as Rikenellaceae, and balanced the gut microbiota by regulating metabolic pathways. SRL may attenuate PF by regulating gut microbiota. This exploratory study establishes the groundwork for investigating the metagenomics of PF.

Behavior of Spoilage Bacterial Communities in Different Cuts of Enshi Black Pork under Refrigerated Storage (4 °C).

The Enshi black pig is a Chinese native breed known for its rich nutrition content and high quality, which has notable traction in the consumer market. In this study, the potential impact of the main commercial cuts from Enshi black pork carcasses (ham, loin, and belly) on the bacteria community of spoiled meat under refrigerated storage (4 °C) was assessed by using a high-throughput sequencing method. Moreover, the spoilage potential of isolated strains from spoiled pork was investigated. The results demonstrated significant differences (p < 0.05) in bacterial community diversity and composition among spoiled ham, loin, and belly samples. Linear discriminant analysis effect size (LEfSe) analysis revealed a total of 20 significantly different potential bacterial biomarkers, with the dominant genera of Pseudomonas, Psychrobacter, Shewanella and Carnobacterium. Additionally, C. divergens THT1-5, isolated from spoiled ham samples, displayed cold adaptation and higher spoilage potential in Enshi black pork. These findings are helpful for identifying key factors contributing to spoilage in Enshi black pork and developing strategies to inhibit bacterial growth during preservation.

Whole-Genome Metagenomic Analysis of the Oral Microbiota in Patients with Obstructive Sleep Apnea Comorbid with Major Depressive Disorder.

Obstructive sleep apnea (OSA) patients commonly experience high rates of depression. This study aims to examine the oral microbiota characteristics of OSA and those with comorbid major depressive disorder (OSA+MDD) patients. Participants were enrolled from Aug 2022 to Apr 2023. Polysomnography, psychiatrist interviews, and scales were used to diagnose OSA and MDD. Oral samples were collected from participants by rubbing swabs on buccal mucosa, palate, and gums. Oral microbiota was analyzed via whole-genome metagenomics and bioinformatic analysis followed sequencing. Venous blood was drawn to detect plasma inflammatory factor levels. The study enrolled 33 OSA patients, 28 OSA+MDD patients, and 28 healthy controls. Significant differences were found in 8 phyla, 229 genera, and 700 species of oral microbiota among the three groups. Prevotellaceae abundance in the OSA and OSA+MDD groups was significantly lower than that in healthy controls. Linear discriminant analysis effect size (LEfSe) analysis showed that Streptococcaceae and Actinobacteria were the characteristic oral microbiota of the OSA and OSA+MDD groups, respectively. KEGG analysis indicates 30 pathways were changed in the OSA and OSA+MDD groups compared with healthy controls, and 23 pathways were changed in the OSA group compared with the OSA+MDD group. Levels of IL-6 in the OSA+MDD group were significantly higher than in the healthy group, correlating positively with the abundance of Schaalia, Campylobacter, Fusobacterium, Alloprevotella, and Candidatus Nanosynbacter in the oral, as well as with Hamilton Anxiety Rating Scale and Hamilton Depression Rating Scale scores. Significant differences in oral microbiota populations and gene function were observed among the three groups. OSA patients were characterized by a decreased abundance of Prevotellaceae and an increased abundance of Streptococcaceae. OSA+MDD patients had an increased abundance of Actinobacteria. IL-6 might regulate the relationship between depression and the oral microbiota in OSA+MDD patients.

Sequence analysis of microbiota in clinical human cases with diabetic foot ulcers from China

BackgroundDiabetic foot ulcers (DFU) seriously threaten the health and quality of life of patients. The microbiota is the primary reason for the refractory and high recurrence of DFU. This study aimed to determine the wound microbiota at different DFU stages. MethodsWound samples were collected from 48 patients with DFU and divided into three phases: inflammatory (I, n = 49), proliferation (P, n = 22), and remodeling (R, n = 19). The wound samples obtained at different stages were then subjected to 16S rRNA gene sequencing. The number of operational taxonomic units (OTUs) in the different groups was calculated according to the criterion of 97 % sequence similarity. The diversity of the microbiota differentially presented bacterial taxa at the phylum and genus levels, and important phyla and genera in the different groups were further explored. ResultsAfter sequencing, 3351, 925, and 777 OTUs were observed in groups I, P, and R, respectively, and 175 OTUs overlapped. Compared with the inflammatory stage, the α-diversity of wound microbiota at proliferation and remodeling stages was significantly decreased (P < 0.05). At the phylum level, Firmicutes, Proteobacteria, Actinobacteriota, and Bacteroidota were the dominant phyla, accounting for more than 90 % of all the phyla. At the genus level, Random Forest and linear discriminant analysis effect size analyses showed that Peptoniphilus, Lactobacillus, Prevotella, Veillonella, Dialister, Streptococcus, and Ruminococcus were the signature wound microbiota for the inflammatory stage; Anaerococcus, Ralstonia, Actinomyces, and Akkermansia were important species for the proliferation stage; and the crucial genera for the remodeling stage were Enterobacter, Pseudomonas, Sondgrassella, Bifidobacterium, and Faecalibacterium. ConclusionsThere were significant differences in the composition and structure of the wound microbiota in patients with DFU at different stages, which may lay a foundation for effectively promoting wound healing in DFU.

Microbial community dynamics and nitrogen transformation associated with turbid-turned culture stage of Pacific white shrimp, Litopenaeus vannamei in small greenhouse farms

Small greenhouse farms have experienced rapid expansion of Litopenaeus vannamei culture in China in recent years. To investigate microbial community dynamics and nitrogen transformation during the early critical stage, known as the turbid-turned stage in small greenhouse farms, microbial samples from the water column of small greenhouses were analyzed by 16S rRNA and 18S rRNA high-throughput sequencing, along with the detection of ammonia nitrogen in water. The results of water quality analysis revealed that accumulated ammonia nitrogen was converted to nitrite as the water color transitioned from clear green to turbid brown. High-throughput sequencing data demonstrated a shift in dominant microorganisms from zooplankton to algae and bacteria during the turbid-turned stage, and the main functional microbial taxa, such Marivita and Chlorella, were enriched. The results of Linear Discriminant Analysis Effect Size and canonical correlation analyses indicated that the compositions of key microbial communities were correlated with environmental factors. Furthermore, analysis of functional genes indicated that ammonia-oxidizing bacteria were present in the early growth stage, while the abundance of nitrite-oxidizing bacteria was low during the early culture stage. Overall, the findings suggest that microorganisms during the turbid-turned stage in small greenhouses may play a crucial role in regulating water quality and promoting shrimp health within a stable small greenhouse environment.

The bacterial community drive the humification and greenhouse gas emissions during plant residues composting under different aeration rates

ABSTRACT This study investigated the effects of different aeration intensities on organic matter (OM) degradation, greenhouse gas emissions (GHG) as well as humification during plant residue composting. Three intermittent aeration intensities of 0.084 (T low), 0.19 (T medium) and 0.34 (T high) L min−1kg−1 DM with 30 min on/30 min off were conducted on a lab-scale composting experiment. Results showed that OM mineralization in T high was more evident than T low and T medium, resulting in the highest humic acid content. Humic acid content in T medium and T high was 15.7% and 18.5% higher than that in T low. The average O2 concentration was 4.9%, 9.5% and 13.6% for T low, T medium and T high. Compared with T medium and T high, T low reduced CO2 and N2O emissions by 18.3%–39.6% and 72.4%–63.9%, but the CH4 emission was highest in T low. But the total GHG emission was the lowest in T high. Linear Discriminant Analysis Effect Size analysis showed that the core bacteria within T low mainly belonged to Anaerolineaceae, which was significantly negatively correlated to the emission of CH4. Thermostaphylospora, Unclassified_Vicinamibacteraceae and Sulfurifustis were identified as core bacteria in T medium and T high, and these genus were significantly postively correlated to CO2 and N2O emissions. Redundancy analysis showed that total orgnic carbon, O2 and electrical conductivity were the key factors affecting the evolution of bacterial community.

BIOM-05. THE GUT-MICROBIOTA COMPOSITION IN PEDIATRIC BRAIN TUMORS: AN EMERGING CRUCIAL PLAYER

Abstract BACKGROUND Central nervous system (CNS) tumors represent the main cause of cancer-related deaths in children diagnosed at 0–14 years. It has been demonstrated that the bidirectional interaction between gut microbiota and brain, called microbiota-gut-brain axis, has a key role in pathophysiological processes, mediating proliferation of brain tumor cells. The aim of this study was to determine whether the gut microbiota composition of pediatric patients affected by CNS tumors has peculiarities. METHODS We included 42 pediatric patients from the clinical study NET-2019-12371188 that were divided in two groups: i) 12 affected by SNC tumors (group 1); ii) 30 affected by other tumor types (group 2), non related to CNS. From their stool samples, microbial DNA was extracted, 16S DNA libraries were generated and sequenced on IONS5xl (ThermoFisher). From the resulting operational taxonomic unit (OTU) tables, the composition of gut-microbiota was analyzed. RESULTS To determine the richness of gut microbiota in terms of different taxa, alpha diversity analysis was performed. We applied the number of observed features as data matrix and it was lower in group 1 compared to group 2 (p-value= 0.003); on the other side, the homogeneity of taxonomic groups was determined by Pielou’s evenness index, that was higher in group 1 (p-value=0.018), compared to group 2. Beta-diversity measured with unweighted UniFrac metrics revealed that the taxonomic and phylogenetics composition of gut microbiota is different between group 1 and 2 (p-value= 0.03). Finally, linear discriminant analysis effect size (LEfSe) revealed an increase of genus from RF32 order in group 1, while in group 2 genus Blautia ad genus from Coriobacteriaceaea family increased. CONCLUSIONS In conclusion, gut microbiota has a peculiar composition in pediatric patients affected by CNS tumors.

Bacterial Communities, Network Complexity, and Multifunctionality Affected by Soil Types in Northeastern China

The Northeast China Plain (NCP) is the country’s most important grain-producing area. Unraveling how bacterial communities in this region assemble and distribute according to soil type is essential for sustainable agricultural development and optimizing the precise management of soil resources. In this study, 106 soil samples were collected from three typical zonal soil types (black calcium soil (BCS), black soil (BS), and dark brown soil (DBS)) spanning from west to east in the NCP. By combining soil field surveys and high-throughput microbial sequencing analysis, we found that bacterial diversity and community structure differed significantly by soil type. Proteobacteria, Gemmatimonadetes, and Acidobacteria were enriched in BCS, BS, and DBS, respectively. Compared to BSC and DBS, BS had the highest nutrient concentration and most neutral pH values, which may recruit more diverse bacterial communities and construct a more connected ecological network. Network analysis further identified Burkholderiales, Sphingomonadales, and SC_I_84 as key hubs in BS, BCS, and BCS, respectively. The majority of classified hubs consistent with the results of the linear discriminant analysis effect size belonged to the predominant biomarkers. Redundancy and Mantel test analyses revealed that the bacterial composition in various soil types showed distinctive responses to heterogeneity in soil physicochemical properties. Soil pH and TP were the primary factors shaping the soil bacterial community structure in these three soil types on the NCP. Moreover, bacterial composition and diversity were strongly related to changes in soil multifunctionality in BCS, and the relative abundances of three classes (TM1, Opitutae, and Deinococci) were the most important biotic variables for predicting BCS ecosystem multifunctionality. In summary, our results suggest that soil type variation has a strong influence in terms of shaping bacterial community structure and affecting soil multifunctionality. Correspondingly, diverse co-occurrence patterns were observed in different soil types.

Emergence of rare and low abundant anaerobic gut Firmicutes is associated with a significant downfall of Klebsiella in human colon cancer

Gut bacterial dysbiosis has been linked to several gastrointestinal diseases, including deadly colorectal cancer (CRC), a leading cause of mortality in cancer patients. However, perturbation in gut bacteriome during colon cancer (CC, devoid of colorectal malignancy) remains poorly explored. Here, 16S rRNA gene amplicon sequencing was carried out for fecal DNA samples targeted to hypervariable V3–V4 region by employing MiSeq platform to explore the gut bacterial community shift in CC patients. While alpha diversity indices predicted high species richness and diversity, beta diversity showed marked gut bacterial compositional dissimilarity in CC versus healthy controls (HC, n = 10 each). We observed a significant (p < 0.05, Wilcoxon Rank-Sum test) emergence of low-abundant anaerobic taxa, including Parvimonas and Peptostreptococcus, in addition to Subdoligranulum, Coprococcus, Holdemanella, Solobacterium, Bilophila, Blautia, Dorea, Moryella and several unidentified taxa, mainly affiliated to Firmicutes, in CC patients. In addition, we also traced the emergence of putative probiotic taxon Slackia, belonging to Actinomycetota, in CC patients. The emergence of anaerobic Firmicutes in CC is accompanied by a significant (p < 0.05) decline in the Klebsiella, as determined through linear discriminant analysis effect size (LEfSe) and heat tree analyses. Shifts in core microbiome and variation in network correlation were also witnessed. Taken together, this study highlighted a significant and consistent emergence of rare anaerobic Firmicutes suggesting possible anaerobiosis driving gut microbial community shift, which could be exploited in designing diagnostic and therapeutic tools targeted to CC.

Analysis of Gut Microbiota as a Diagnostic Biomarker for Lung Adenocarcinoma with Qi-Deficiency and Phlegm-Turbid Stagnation

Background: In lung adenocarcinoma (LUAD), Qi-deficiency and Phlegm-turbid stagnation (QP) are the most prevalent Traditional Chinese medicine (TCM) syndrome. Methods: Herein, we collected 90 fecal samples (Healthy individual (H): 30; other syndrome (O): 30; QP: 30) and explored the composition and diversity of gut microbiota in LUAD patients with QP syndrome using 16s-rRNA sequencing. Then, we identified biomarkers for QP syndrome in LUAD patients with linear discriminant analysis (LDA) effect size (LEfSe) and applied logistic regression analysis to construct a diagnostic model evaluated with the area under the receiver operating characteristic curve (AUC) and validated with data from metagenomics. Results: The α diversity and β diversity revealed that the microbiota community structure in LUAD patients with QP syndrome was different from that with healthy individuals and LUAD patients with other syndromes. At the phylum level, the QP group had more abundance of Bacteroidetes and less Proteobacteria than the O group. At the genus level, the abundance of 4 genera (Bacteroides, Parabacteroides, Prevotella, and Flavonifractor) was different between the QP group and O group. Moreover, LEfSe indicated that those 4 genera might be the biomarkers for LUAD patients with QP syndrome. Then, we used those 4 genera to develop a diagnostic model. The AUC based on 16s-rRNA sequencing and metagenomics was 0.989 and 1, respectively. Conclusion: A diagnostic model was developed, which would be an available tool for the clinical diagnosis of LUAD with QP syndrome.

Unique microbial communities of parasitic fleas on wild animals from the Qinghai-Tibet Plateau.

Fleas, one of the most significant ectoparasites, play a crucial role as vectors in spreading zoonotic diseases globally. The Qinghai Province, as part of the Qinghai-Tibet Plateau, is one of the provinces in China with the largest number of flea species. In this study, we characterized the microbial communities of eighty-five adult fleas, belonging to nineteen species within four families (Ceratophyllidae, Ctenophthalmidae, Leptopsyllidae, and Pulicidae). We identified a total of 1162 unique operational taxonomic units at the genus level, with flea-borne pathogens such as Wolbachia, Bartonella, Rickettsia being the members of top abundant taxa. Except for comparison between Ctenophthalmidae and Leptopsyllidae families, the analyses of both alpha- and beta- diversity indicators suggested that bacterial diversity varied among flea families. This could be attributed to flea phylogeny, which also influenced by their geographical sites and animal hosts. Results of Linear discriminant analysis effect size (LEfSe) indicated that 29 genera in Ceratophylloidea, 11 genera in Ctenophthalmidae, 15 genera in Leptopsyllidae, and 22 genera in Pulicidae were significantly responsible for explaining the differences among the four flea families (linear discriminant analysis score > 2, P < 0.05). Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2) analyses showed that the functional pathways varied significantly across flea families, which was supported by the significant correlation between the functional pathways and the microbial communities.