The Influence of Age and Sex on Ocular Surface Microbiota in Healthy Adults
Xiaofeng WenMiao LiYuhua DengPaul W. BibleXiao HuYanli ZouYu LiuShixin GuoJuanran LiangTingting ChenGuang-Hua PengWei ChenLingyi LiangLai Wei
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Purpose: A growing body of evidence suggests that the microbiome of the ocular surface confers potent immunoregulatory functions and has a key role in the physiologic maintenance of healthy eyes and in the pathogenesis of ocular diseases. Although the microbiome is known to be affected by age and sex, the influence of these factors on ocular surface microbiota in healthy adults remains largely unknown. Methods: Ocular surface microbiome samples were obtained from the inferior bulbar conjunctiva of 48 young and 42 old adults at Zhongshan Ophthalmic Center. Using metagenomic shotgun sequencing, we characterized the sex- and age-differences in conjunctival microbiome profiles of healthy adults. Results: Male and female groups differed only in the β diversity of bacterial communities, while there were significant differences in bacterial composition, metabolic functions, and the abundance of antibiotic resistance genes between young and old adult groups. Conclusions: Our findings suggest that age and sex collectively shape the conjunctival microbiome, and may change the immune homeostasis of the ocular surface through alterations of its commensal microbiome.Keywords:
Pathogenesis
Abstract The colonization of the human gut microbiome begins at birth, and, over time, these microbial communities become increasingly complex. Most of what we currently know about the human microbiome, especially in early stages of development, was described using culture-independent sequencing methods that allow us to identify the taxonomic composition of microbial communities using genomic techniques, such as amplicon or shotgun metagenomic sequencing. Each method has distinct tradeoffs, but there has not been a direct comparison of the utility of these methods in stool samples from very young children, which have different features than those of adults. We compared the effects of profiling the human infant gut microbiome with 16S rRNA amplicon versus shotgun metagenomic sequencing techniques in 130 fecal samples; younger than 15, 15-30, and older than 30 months of age. We demonstrate that observed changes in alpha-diversity and beta-diversity with age occur to similar extents using both profiling methods. We also show that 16S rRNA profiling identified a larger number of genera and we find several genera that are missed or underrepresented by each profiling method. We present the link between alpha diversity and shotgun metagenomic sequencing depth for children of different ages. These findings provide a guide for selecting an appropriate method and sequencing depth for the three studied age groups.
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Amplicon sequencing
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Human Microbiome Project
Profiling (computer programming)
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The shotgun sequencing data presented in this report are related to the research article named "Gut microbiome shotgun sequencing in assessment of microbial community changes associated with H. pylori eradication therapy" (Khusnutdinova et al., 2016) [1]. Typically, the H. pylori eradication protocol includes a prolonged two-week use of the broad-spectrum antibiotics. The presented data on the whole-genome sequencing of the total DNA from stool samples of patients before the start of the eradication, immediately after eradication and several weeks after the end of treatment could help to profile the gut microbiota both taxonomically and functionally. The presented data together with those described in Glushchenko et al. (2017) [2] allow researchers to characterize the metagenomic profiles in which the use of antibiotics could result in dramatic changes in the intestinal microbiota composition. We perform 15 gut metagenomes from 5 patients with H. pylori infection, obtained through the shotgun sequencing on the SOLiD 5500 W platform. Raw reads are deposited in the ENA under project ID PRJEB21338.
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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.
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Shotgun metagenomics has enabled the discovery of antibiotic resistance genes (ARGs). Although there have been numerous studies benchmarking the bioinformatics methods for shotgun metagenomic data analysis, there has not yet been a study that systematically evaluates the performance of different experimental protocols on metagenomic species profiling and ARG detection. In this study, we generated 35 whole genome shotgun metagenomic sequencing data sets for five samples (three human stool and two microbial standard) using seven experimental protocols (KAPA or Flex kits at 50ng, 10ng, or 5ng input amounts; XT kit at 1ng input amount). Using this comprehensive resource, we evaluated the seven protocols in terms of robust detection of ARGs and microbial abundance estimation at various sequencing depths. We found that the data generated by the seven protocols are largely similar. The inter-protocol variability is significantly smaller than the variability between samples or sequencing depths. We found that a sequencing depth of more than 30M is suitable for human stool samples. A higher input amount (50ng) is generally favorable for the KAPA and Flex kits. This systematic benchmarking study sheds light on the impact of sequencing depth, experimental protocol, and DNA input amount on ARG detection in human stool samples.
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Abstract Shotgun metagenomic sequencing is a valuable tool for the taxonomic and functional profiling of microbial communities. However, this approach is challenging in samples, such as milk, where a low microbial abundance, combined with high levels of host DNA, result in inefficient and uneconomical sequencing. Here we evaluate approaches to deplete host DNA or enrich microbial DNA prior to sequencing using three commercially available kits. We compared the percentage of microbial reads obtained from each kit after shotgun metagenomic sequencing. Using bovine and human milk samples, we determined that host depletion with the MolYsis complete5 kit significantly improved microbial sequencing depth compared to other approaches tested. Importantly, no biases were introduced. Additionally, the increased microbial sequencing depth allowed for further characterization of the microbiome through the generation of metagenome-assembled genomes (MAGs). Furthermore, with the use of a mock community, we compared three common classifiers and determined that Kraken2 was the optimal classifier for these samples. This evaluation shows that microbiome analysis can be performed on both bovine and human milk samples at a much greater resolution without the need for more expensive deep-sequencing approaches.
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The colonization of the human gut microbiome begins at birth, and over time, these microbial communities become increasingly complex. Most of what we currently know about the human microbiome, especially in early stages of development, was described using culture-independent sequencing methods that allow us to identify the taxonomic composition of microbial communities using genomic techniques, such as amplicon or shotgun metagenomic sequencing. Each method has distinct tradeoffs, but there has not been a direct comparison of the utility of these methods in stool samples from very young children, which have different features than those of adults. We compared the effects of profiling the human infant gut microbiome with 16S rRNA amplicon vs. shotgun metagenomic sequencing techniques in 338 fecal samples; younger than 15, 15–30, and older than 30 months of age. We demonstrate that observed changes in alpha-diversity and beta-diversity with age occur to similar extents using both profiling methods. We also show that 16S rRNA profiling identified a larger number of genera and we find several genera that are missed or underrepresented by each profiling method. We present the link between alpha diversity and shotgun metagenomic sequencing depth for children of different ages. These findings provide a guide for selecting an appropriate method and sequencing depth for the three studied age groups.
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Amplicon sequencing
Human Microbiome Project
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Abstract Background: Shotgun metagenomic sequencing is a valuable tool for the taxonomic and functional profiling of microbial communities. However, this approach is challenging in samples, such as milk, where a low microbial abundance, combined with high levels of host DNA, result in inefficient and uneconomical sequencing. Results: Here we evaluate approaches to deplete host DNA or enrich microbial DNA prior to sequencing using three commercially available kits. We compared the percentage of microbial reads obtained from each kit after shotgun metagenomic sequencing. Using bovine and human milk samples, we determined that host depletion with the MolYsis complete5 kit significantly improved microbial sequencing depth compared to other approaches. Importantly, no biases were introduced. Additionally, the increased microbial sequencing depth allowed for further characterization of the microbiome through the generation of metagenome-assembled genomes (MAGs). Conclusions: This evaluation shows that microbiome analysis can be performed on both bovine and human milk samples at a much greater resolution without the need for more expensive deep-sequencing approaches.
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Over the last decade, it has become increasingly apparent that the microbiome is a central component in human well-being and illness. However, to establish innovative therapeutic methods, it is crucial to learn more about the microbiota. Thereby, the area of metagenomics and associated bioinformatics methods and tools has become considerable in the study of the human microbiome biodiversity. The application of these metagenomics approaches to studying the gut microbiome in COVID-19 patients could be one of the promising areas of research in the fight against the SARS-CoV-2 infection and disparity. Therefore, understanding how the gut microbiome is affected by or could affect the SARS-CoV-2 is very important. Herein, we present an overview of approaches and methods used in the current published studies on COVID-19 patients and the gut microbiome. The accuracy of these researches depends on the appropriate choice and the optimal use of the metagenomics bioinformatics platforms and tools. Interestingly, most studies reported that COVID-19 patients’ microbiota are enriched with opportunistic microorganisms. The choice and use of appropriate computational tools and techniques to accurately investigate the gut microbiota is therefore critical in determining the appropriate microbiome profile for diagnosis and the most reliable antiviral or preventive microbial composition.
2019-20 coronavirus outbreak
Gut microbiome
Pandemic
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Sequence assembly
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