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2021 ◽  
Author(s):  
Deepthi M ◽  
Kumar Arvind ◽  
Rituja Saxena ◽  
Joby Pulikkan ◽  
Vineet K Sharma ◽  
...  

Abstract The indigenous cattle are efficient in converting low quality feeds and forage into animal products. Kasaragod Dwarf cattle, a unique non-descriptive native cattle of Kerala, India, are noted for their unique qualities, such as low feed intake, thermotolerance, greater resistance to diseases and A2 allelic variant milk. However, owing to the higher milk yield, Holstein crossbred cattle are given more importance over Kasaragod Dwarf. The hindgut microbiota plays a major role in various biological processes such as the digestion, vitamins synthesis, and immunity in cattle. In this study, we compared the hindgut microbiota of the Kasaragod Dwarf with the highly found, Holstein crossbred utilizing 16S rRNA high-throughput sequencing for a better understanding of the relationship between the host and microbial community. Four replicates of each 20 samples comprising two cattle type (n=10) were sequenced and analyzed. Marker gene-based taxonomic analysis affirmed variations in their microbial composition. Principle Coordinate Analysis (PCoA) using weighted and unweighted UniFrac distance matrices showed the distinct microbial architecture of the two cattle type. Random Forest analysis further confirmed the distinctness and revealed the signature taxa in K-Dwarf. The study observed the predominance of feed efficiency associated genera viz., Anaerovibrio, Succinivibrio, Roseburia, Coprococcus, Anaerostipes, Paludibacter, Elusimicrobium, Sutterella, Oribacterium, Coprobacillus, and Ruminobacter in Kasaragod Dwarf cattle. The study highlights the abundance of unique and beneficial hindgut microflora found in Kasaragod Dwarf, which may attest its importance over exotic cattle breeds viz., Holstein. To our knowledge, this is the first report of Kasaragod Dwarf cattle gut microbiome profiling. This study is pivotal towards developing genetic resources for the microbial population in K-Dwarf and how it could be differentiated from Holstein crossbred cattle.


2021 ◽  
Author(s):  
Yushu Shi ◽  
Liangliang Zhang ◽  
Christine Peterson ◽  
Kim-Anh Do ◽  
Robert Jenq

Abstract Background: In microbiome data analysis, unsupervised clustering is often used to identify naturally occurring clusters, which can then be assessed for associations with characteristics of interest. In this work, we systematically compared beta diversity and clustering methods commonly used in microbiome analyses. We applied these to four published datasets where highly distinct microbiome profiles could be seen between sample groups, as well a clinical dataset with less clear separation between groups. Results: Although no single method outperformed the others consistently, we did identify key scenarios where certain methods can underperform. Specifically, the Bray Curtis (BC) metric resulted in poor clustering in a dataset where high-abundance OTUs were relatively rare. In contrast, the unweighted UniFrac (UU) metric clustered poorly on dataset with a high prevalence of low-abundance OTUs. To explore these hypotheses about BC and UU, we systematically modified properties of the poorly performing datasets and found that this approach resulted in improved BC and UU performance. Based on these observations, we rationally combined BC and UU to generate a novel metric. We tested its performance while varying the relative contributions of each metric and also compared it with another combined metric, the generalized UniFrac distance. The proposed metric showed high performance across all datasets. Conclusions Our systematic evaluation of clustering performance in these five datasets demonstrates that there is no existing clustering method that universally performs best across all datasets. We propose a combined metric of BC and UU that capitalizes on the complementary strengths of the two metrics.


2021 ◽  
Vol 9 (10) ◽  
pp. 2095
Author(s):  
Yasser Mohamed ◽  
Masafumi Uematsu ◽  
Yoshitomo Morinaga ◽  
Hien-Anh Thi Nguyen ◽  
Michiko Toizumi ◽  
...  

Acute bacterial conjunctival infections are common, and this study identified the conjunctival bacterial community in infectious conjunctivitis cases seen at the outpatient clinic of Khanh Hoa General Hospital in Nha Trang, Vietnam from October 2016 through December 2017. Conjunctival swabs were collected and tested using conventional culture, PCR, and 16S ribosomal RNA sequencing. The study included 47 randomly selected patients. More than 98% of all DNA reads represented five bacterial phyla. Three of these phyla constituted 92% of all sequences (Firmicutes (35%), Actinobacteria (31%), and Proteobacteria (26%)). At the genus level, there were 12 common genera that constituted about 61% of all sequence reads. Seven of those genera were common (Streptococcus (10%), Cutibacterium (10%), Staphylococcus (7%), Nocardioides (7%), Corynebacterium 1 (5%), Anoxybacillus (5%), and Acinetobacter (5%)), which encompassed 49% of all reads. As for diversity analysis, there was no difference on PERMANOVA analysis (unweighted UniFrac) for sex (p = 0.087), chemosis (p = 0.064), and unclassified eyedrops (p = 0.431). There was a significant difference in cases with bilateral conjunctivitis (p = 0.017) and for using antibiotics (p = 0.020). Of the predominant phyla, Firmicutes had the highest abundance in bacterial conjunctivitis in this study. Pseudomonas as a resident commensal microbiota may have an important role in the prevention of infection.


2021 ◽  
Author(s):  
Michi Omori ◽  
Kato-kogoe Nahoko ◽  
Shoichi Sakaguchi ◽  
Eri Komori ◽  
Kazuya Inoue ◽  
...  

Abstract Background Recently, the gut microbiota has been shown to play an important role in the response and resistance to chemotherapy. Although there is much knowledge about chemotherapy-induced changes in the gut microbiota, chemotherapy-associated changes in the oral microbiota remain unclear. Herein, we aimed to evaluate the changes in oral microbiota associated with the initiation of chemotherapy in patients with malignant hematopoietic tumors. Methods Oral samples were collected before and 8–20 days after the start of chemotherapy from 50 patients with malignant hematopoietic tumors who were starting chemotherapy for the first time. The 16S ribosomal RNA gene sequencing of bacterial DNA extracted from oral samples was performed to compare the oral microbiota before and after the initiation of chemotherapy. Results The richness or evenness of diversity in the ‘after start of chemotherapy’ group decreased significantly, compared with the ‘before start of chemotherapy’ group (alpha-diversity; observed operational taxonomic units (OTUs) index, p < 0.001; and Shannon’s index, p < 0.001). The overall salivary microbiota structure between the pre- and post-chemotherapy groups differed significantly (beta-diversity; unweighted UniFrac distances, p = 0.001; and weighted UniFrac distances, p = 0.003). Linear discriminant analysis effect size analysis demonstrated an increased abundance of species of certain genera, such as Staphylococcus, and decreased abundance of species of some genera, such as Streptococcus and Neisseria, in the ‘after-chemotherapy’ group, compared with those in the ‘before-chemotherapy’ group. The amounts and trends of change in the oral microbiota before and after the start of chemotherapy differed among the subjects. Of the 25 bacterial genera whose prevalence changed significantly before and after the start of chemotherapy, the proportion of oral commensals such as Streptococcus and Neisseria decreased in many subjects. In contrast, Staphylococcus and Pseudomonas were detected only in a few subjects, but their relative abundance increased significantly after the start of chemotherapy. Conclusions The oral microbiota of patients with hematopoietic tumors changed markedly after the initiation of chemotherapy. Our findings are expected to aid the elucidation of the pathogenesis of oral mucositis, which is an adverse event of chemotherapy, and the development of treatment methods for this condition.


2021 ◽  
Author(s):  
Deepthi M ◽  
Kumar Arvind ◽  
Rituja Saxena ◽  
Joby Pulikkan ◽  
Shamjana U ◽  
...  

Abstract The indigenous cattle are efficient in converting low quality feeds and forage into animal products. Kasaragod Dwarf (K-Dwarf) cattle, a non-descriptive native cattle variety of Kerala, are noted for their unique qualities, like short stature, low feed intake, thermotolerance, greater resistance to diseases and A2 allelic variant milk. This study hypothesizes that K-Dwarf cow relies on their unique hindgut microbes to ferment the low quality feeds into the efficient animal product. To compare and contrast this unique microbiota and their relationship between the host, we performed microbial profiling of the two genetically distinct cattle-type viz., K-Dwarf, and Holstein utilizing 16S rRNA high-throughput sequencing. Principle Coordinate Analysis using weighted and unweighted UniFrac distance matrices showed significantly distinct clustering of K-Dwarf microbial community compared to Holstein, implying the distinct microbial architecture that K-Dwarf harbors. The dissimilarities observed between the two cattle types were further revealed from the signature taxa identified in each cattle type following Random Forest analysis. In addition, the study observed the predominance of feed efficiency associated genera viz., Anaerovibrio, Succinivibrio, Roseburia, Coprococcus, Anaerostipes, Paludibacter, Elusimicrobium, Sutterella, Oribacterium, Coprobacillus, and Ruminobacter in K-Dwarf cattle. The study highlights the abundance of unique and beneficial hindgut microflora found in K-Dwarf, which may attest its importance over exotic cattle breeds viz., Holstein. To our knowledge, this is the first report of K-Dwarf cattle gut microbiome profiling. Further molecular characterization is solicited to better understand the microbial role in the conversion of low-quality feeds into more efficient animal products, a well-defined characteristic of indigenous cattle.


2021 ◽  
Author(s):  
Yi-Juan Hu ◽  
Glen A. Satten

Abstract Background PERMANOVA [1] is currently the most commonly used method for testing community-level hypotheses about microbiome associations with covariates of interest. PERMANOVA can test for associations that result from changes in which taxa are present or absent by using the Jaccard or unweighted UniFrac distance. However, such presence-absence analyses face a unique challenge: confounding by library size (total sample read count), which occurs when library size is associated with covariates in the analysis. It is known that rarefaction (subsampling to a common library size) controls this bias, but at the potential costs of information loss and the introduction of a stochastic component into the analysis.Methods Here we develop a non-stochastic approach to PERMANOVA presence-absence analyses that aggregates information over all potential rarefaction replicates without actual resampling, when the Jaccard or unweighted UniFrac distance is used. We compare this new approach to three possible ways of aggregating PERMANOVA over multiple rarefactions obtained from resampling: averaging the distance matrix, averaging the (element-wise) squared distance matrix, and averaging the F-statistic.Results Our simulations indicate that our non-stochastic approach is robust to confounding by library size and outperforms each of the stochastic resampling approaches. We also show that, when overdispersion is low, averaging the (element-wise) squared distance outperforms averaging the unsquared distance, currently implemented in the R package vegan. We illustrate our methods using an analysis of data on inflammatory bowel disease (IBD) in which samples from case participants have systematically smaller library sizes than samples from control participants.Conclusions Our extension of PERMANOVA for presence-absence analyses using a non-stochastic approach that aggregates information over all potential rarefaction replicates without actual resampling is robust to confounding by library size and outperforms stochastic resampling approaches.


2021 ◽  
Author(s):  
Chunxiao Chen ◽  
Zehai Huang ◽  
Pengcheng Huang ◽  
Kun Li ◽  
Jiarong Zeng ◽  
...  

Abstract Background Urinary microbiota is associated with the recurrence of bladder cancer, but the underlying mechanism remains unclear. The notion that microbiota can upregulate PD-L1 expression in tumors to promote immune escape have been demonstrated. We hypothesized that the urinary microbiota may be involved in the recurrence and progression of non-muscle invasive bladder cancer (NMIBC) by upregulating the PD-L1 expression. For proving this hypothesis, we firstly performed this study to characterize the potential urinary microbial community possibly associated with PD-L1 expression in male patients with NMIBC. Results The subjects (aged 43–79 years) based on their PD-L1 immunohistochemical results were divided into PD-L1-positive group (P group) and PD-L1-negative group (N group) respectively. We observed that P group exhibited higher species richness and diversity (based on Observed species and Ace index, both P < 0.05). Significantly different composition of urinary microbiota was found between P group and N group (based on weighted Unifrac and unweighted Unifrac distances metric, both P < 0.05). Enrichment of some bacterial genera (e.g., Leptotrichia, Roseomonas, and Propionibacterium) and decrease of some bacterial genera (e.g.,Prevotella and Massilia) were observed in P group as compared with N group. These findings indicate that these genera may affect the expression of PD-L1 through some mechanisms to be studied. PICRUSt analysis showed that several pathways involved in the metabolism of chemical compounds and immune-related disease were enriched in the PD-L1 negative group. Conclusion Our data indicate that urinary microbiota may be an important determinant of PD-L1 expression in male NMIBC patients. The findings of our study may facilitate subsequent study on the role and mechanism of urinary microbiota in the recurrence of NMIBC and may also pave a new way for the better application of PD1 or PD-L1 blockers in bladder cancer in the future.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Susana Seixas ◽  
Allison R. Kolbe ◽  
Sílvia Gomes ◽  
Maria Sucena ◽  
Catarina Sousa ◽  
...  

AbstractThe lung is inhabited by a diverse microbiome that originates from the oropharynx by a mechanism of micro-aspiration. Its bacterial biomass is usually low; however, this condition shifts in lung cancer (LC), chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD). These chronic lung disorders (CLD) may coexist in the same patient as comorbidities and share common risk factors, among which the microbiome is included. We characterized the microbiome of 106 bronchoalveolar lavages. Samples were initially subdivided into cancer and non-cancer and high-throughput sequenced for the 16S rRNA gene. Additionally, we used a cohort of 25 CLD patients where crossed comorbidities were excluded. Firmicutes, Proteobacteria and Bacteroidetes were the most prevalent phyla independently of the analyzed group. Streptococcus and Prevotella were associated with LC and Haemophilus was enhanced in COPD versus ILD. Although no significant discrepancies in microbial diversity were observed between cancer and non-cancer samples, statistical tests suggested a gradient across CLD where COPD and ILD displayed the highest and lowest alpha diversities, respectively. Moreover, COPD and ILD were separated in two clusters by the unweighted UniFrac distance (P value = 0.0068). Our results support the association of Streptoccocus and Prevotella with LC and of Haemophilus with COPD, and advocate for specific CLD signatures.


Author(s):  
Naoki Toyama ◽  
Daisuke Ekuni ◽  
Daisuke Matsui ◽  
Teruhide Koyama ◽  
Masahiro Nakatochi ◽  
...  

Few studies have exhaustively assessed relationships among polymorphisms, the microbiome, and periodontitis. The objective of the present study was to assess associations simultaneously among polymorphisms, the microbiome, and periodontitis. We used propensity score matching with a 1:1 ratio to select subjects, and then 22 individuals (mean age ± standard deviation, 60.7 ± 9.9 years) were analyzed. After saliva collection, V3-4 regions of the 16S rRNA gene were sequenced to investigate microbiome composition, alpha diversity (Shannon index, Simpson index, Chao1, and abundance-based coverage estimator) and beta diversity using principal coordinate analysis (PCoA) based on weighted and unweighted UniFrac distances. A total of 51 single-nucleotide polymorphisms (SNPs) related to periodontitis were identified. The frequencies of SNPs were collected from Genome-Wide Association Study data. The PCoA of unweighted UniFrac distance showed a significant difference between periodontitis and control groups (p < 0.05). There were no significant differences in alpha diversity and PCoA of weighted UniFrac distance (p > 0.05). Two families (Lactobacillaceae and Desulfobulbaceae) and one species (Porphyromonas gingivalis) were observed only in the periodontitis group. No SNPs showed significant expression. These results suggest that periodontitis was related to the presence of P. gingivalis and the families Lactobacillaceae and Desulfobulbaceae but not SNPs.


PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11490
Author(s):  
Fuhua Zhang ◽  
Na Xu ◽  
Wenhua Wang ◽  
Yishuang Yu ◽  
Shibao Wu

Background The gut microbiomes of mammals are closely related to the diets of their hosts. The Sunda pangolin (Manis javanica) is a specialized myrmecophage, but its gut microbiome has rarely been studied. Methods Using high-throughput Illumina barcoded 16S rRNA amplicons of nine fecal samples from nine captive Sunda pangolins, we investigated their gut microbiomes. Results The detected bacteria were classified into 14 phyla, 24 classes, 48 orders, 97 families, and 271 genera. The main bacterial phyla were Firmicutes (73.71%), Proteobacteria (18.42%), Actinobacteria (3.44%), and Bacteroidetes (0.51%). In the PCoA and neighbor-net network (PERMANOVA: pangolins vs. other diets, weighted UniFrac distance p < 0.01, unweighted UniFrac distance p < 0.001), the gut microbiomes of the Sunda pangolins were distinct from those of mammals with different diets, but were much closer to other myrmecophages, and to carnivores, while distant from herbivores. We identified some gut microbiomes related to the digestion of chitin, including Lactococcus, Bacteroides, Bacillus, and Staphylococcus species, which confirms that the gut microbiome of pangolins may help them to digest chitin. Significance The results will aid studies of extreme dietary adaption and the mechanisms of diet differentiation in mammals, as well as metagenomic studies, captive breeding, and ex situ conservation of pangolins.


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