{"id":211,"date":"2021-09-01T13:39:39","date_gmt":"2021-09-01T13:39:39","guid":{"rendered":"https:\/\/website.prod.unilu.spikeseed.cloud\/lcsb-fr\/news\/combining-sequencing-approaches-and-omics-to-characterise-microbiomes\/"},"modified":"2021-09-01T13:39:39","modified_gmt":"2021-09-01T13:39:39","slug":"combining-sequencing-approaches-and-omics-to-characterise-microbiomes","status":"publish","type":"news","link":"https:\/\/www.uni.lu\/lcsb-fr\/news\/combining-sequencing-approaches-and-omics-to-characterise-microbiomes\/","title":{"rendered":"Combining sequencing approaches and omics to characterise microbiomes"},"content":{"rendered":"

DNA contains the blueprint for life, be it for mammals, plants or microorganisms. Thanks to current technologies, DNA can be extracted from virtually\u00a0any environment, including\u00a0mixed communities\u00a0of\u00a0microorganisms\u00a0like a microbiome, and then sequenced. Sequencing produces what could be described as small copies of different parts of the blueprint. A software is then used to reconstruct the original blueprint, i.e., to which genes the different DNA sequences contained in a sample correspond. This is called a metagenomic reconstruction. It allows researchers to\u00a0identify genes of interest and to understand the composition and functions of microbiomes. As technologies are fast evolving, scientists have now at their disposal different sequencing approaches and software to generate these metagenomic reconstructions. In an\u00a0article recently published in\u00a0Briefings in Bioinformatics<\/a>, researchers of the Luxembourg Centre for Systems Biomedicine (LCSB) at the University of Luxembourg and from the Luxembourg Institute of Science and Technology (LIST) investigate how these different approaches impact the reconstruction and downstream analyses of microbiomes. They show that different sequencing technologies \u2013 long-read or short-read \u2013 as well as assembly strategies, meaning the choice of software used for the reconstruction of either long-read data, short-read data, or both in a hybrid approach, can lead to\u00a0different conclusions. This is especially relevant as the use of\u00a0emerging long-read sequencing\u00a0technologies\u00a0will increase in the future and discrepancies between approaches will need to be addressed. These findings pave the way for critical assessments of metagenomic reconstructions.<\/p>\n

\nConstant evolution in sequencing technologies<\/h2>\n

Sequencing technologies have come a long way. The first generation \u2013 Fred Sanger\u2019s chain-termination method \u2013 was first described in 1977 and became the main technology for sequencing over the next decades. A second generation was launched in 2005 with the arrival of next-generation sequencing (NGS), new techniques that lowered the costs and increased throughput. Despite these improvements, NGS technologies have a common limitation: the inability to sequence long stretches of DNA, hence they are also referred to as \u201cshort-read sequencing\u201d (SRS) technologies.<\/p>

Third-generation sequencing, also called long-read sequencing (LRS), is now emerging and tackles several of the shortcomings of the second generation. With LRS, read lengths can reach over 10 kilobase pairs and it is possible to resolve complex and repetitive loci in genomes. \u201cLRS is considered to be the next frontier of genomics,\u201d details\u00a0Dr\u00a0Susheel Bhanu Busi<\/a>, joint-first author of the article along\u00a0Dr\u00a0Valentina Galata<\/a>. \u201cAs it is especially relevant to study microbial populations, our research group at the LCSB was very interested in testing and assessing this new technology.\u201d<\/p>

\n \n\"\"\n <\/figure>\n

\nShort-reads, long-reads and hybrid<\/h2>\n

Despite the promises of LRS, previous studies have shown that its accuracy remains lower compared to SRS and that error-correction steps are needed. Hybrid (HY) assembly methods using both SRS and LRS have been proposed to reduce the error rate while leveraging the increased read contiguity but the overall impact of the sequencing and assembly methods chosen to reconstruct the genes in a microbial community is not well understood.<\/p>

Researchers from the\u00a0Systems Ecology group<\/a>\u00a0and\u00a0Bioinformatics Core<\/a>\u00a0at the LCSB and colleagues from the\u00a0LIST<\/a>\u00a0evaluated short-read-only, long-read-only and hybrid assembly approaches in four different metagenomic samples of varying complexity: a mock community, a natural whey starter culture, a cow rumen sample and a novel dataset from a human faecal sample. \u201cWe wanted to understand how sample diversity and assembly approach are linked, and address the influence of sequencing technologies,\u201d explains\u00a0Dr C\u00e9dric Christian Laczny<\/a>, senior author of the article.<\/p>

The results of the comparisons carried out by the researchers reveal that short-read, long-read and hybrid approaches not only differ markedly in their overall performance, but also influence the prediction of genes and proteins. The discrepancies observed between the assemblies based on SRS, LRS and HY could impact phylogenetic and functional studies based on these reconstructions, especially when the differences concern functionally relevant genes such as antimicrobial resistance genes.<\/p>

\u201cOur results demonstrate that, irrespective of sample diversity, the sequencing approach and assembly strategy can have a significant impact on the characterisation of the microbiome\u2019s functional potential,\u201d says Dr Valentina Galata. \u201cThey also highlight the complementarity of\u00a0long-read\u00a0and short-read data: they can\u00a0be combined to\u00a0validate predictions and\u00a0provide\u00a0high-confidence reconstructions\u201d<\/p>\n

\nComplementary omics are key for functional analyses<\/h2>\n

Leveraging the System Ecology group\u2019s experience in meta-omics studies of microbiomes, the researchers generated metatranscriptomic and metaproteomic data for one of the four studied samples. They used this data to assess how this complementary information on the microorganisms\u2019 RNA, peptides and proteins, respectively, could be used to\u00a0to resolve\u00a0discrepancies between assembly approaches, for an improved study of\u00a0the functional profile\u00a0of the microbiome. Their results show that the incorporation of meta-omics data\u00a0have a synergistic effect on protein verification and enable critical assessment of metagenome reconstructions. This\u00a0is the first\u00a0study\u00a0to\u00a0integrate\u00a0meta-omics data in combination with long-read sequencing data and\u00a0to\u00a0demonstrate\u00a0the added value that this combination brings to study microbiomes.<\/p>

\n \n\"\"\n <\/figure>\n

\nA combined approach to get a better overview of microbiomes<\/h2>\n

To tackle the discrepancies between sequencing and assembly strategies, the authors propose a reference-independent approach that will help to identify high-confidence genomic reconstructions. It makes use of the synergies between multiple sequencing technologies and allows a more comprehensive integration of meta-omics data.<\/p>

\u201cPast\u00a0studies\u00a0using long-read sequencing data have focussed on reconstructing the genomes\u00a0of\u00a0the most abundant organisms but have ignored large portions of the microbial community by doing so.\u00a0We aim to get a better understanding of the entire community rather than a few select members,\u201d concludes Dr\u00a0C\u00e9dric\u00a0C.\u00a0Laczny. \u201cThis new approach will be\u00a0highly relevant\u00a0to achieve this as it will help us to get more reliable insights into the\u00a0microbiomes\u2019 compositions and functions.\u00a0\u00bb<\/p>

—<\/p>

Reference: Valentina Galata, Susheel Bhanu Busi, Beno\u00eet Josef Kunath, Laura de Nies, Magdalena Calusinska, Rashi Halder, Patrick May, Paul Wilmes, C\u00e9dric Christian Laczny,\u00a0Functional meta-omics provide critical insights into long- and short-read assemblies<\/a>, Briefings in Bioinformatics, 2021.\u00a0https:\/\/doi.org\/10.1093\/bib\/bbab330<\/a><\/p>

Illustration by Valentina Galata.<\/p><\/div><\/section>","protected":false},"excerpt":{"rendered":"

DNA contains the blueprint for life, be it for mammals, plants or microorganisms. Thanks to current technologies, DNA can be extracted from virtually\u00a0any environment, including\u00a0mixed communities\u00a0of\u00a0microorganisms\u00a0like a microbiome, and then sequenced. Sequencing produces what could be described as small copies of different parts of the blueprint. A software is then used to reconstruct the original blueprint, i.e., to which genes the different DNA sequences contained in a sample correspond. This is called a metagenomic reconstruction. It allows researchers to\u00a0identify genes of interest and to understand the composition and functions of microbiomes. As technologies are fast evolving, scientists have now at their disposal different sequencing approaches and software to generate these metagenomic reconstructions. In an\u00a0article recently published in\u00a0Briefings in Bioinformatics, researchers of the Luxembourg Centre for Systems Biomedicine (LCSB) at the University of Luxembourg and from the Luxembourg Institute of Science and Technology (LIST) investigate how these different approaches impact the reconstruction and downstream analyses of microbiomes. They show that different sequencing technologies \u2013 long-read or short-read \u2013 as well as assembly strategies, meaning the choice of software used for the reconstruction of either long-read data, short-read data, or both in a hybrid approach, can lead to\u00a0different conclusions. This is especially relevant as the use of\u00a0emerging long-read sequencing\u00a0technologies\u00a0will increase in the future and discrepancies between approaches will need to be addressed. These findings pave the way for critical assessments of metagenomic reconstructions.<\/p>\n","protected":false},"author":0,"featured_media":212,"template":"","format":"standard","meta":{"featured_image_focal_point":[],"show_featured_caption":false,"ulux_newsletter_groups":"","uluxPostTitle":"","uluxPrePostTitle":"","_trash_the_other_posts":false,"_price":"","_stock":"","_tribe_ticket_header":"","_tribe_default_ticket_provider":"","_tribe_ticket_capacity":"0","_ticket_start_date":"","_ticket_end_date":"","_tribe_ticket_show_description":"","_tribe_ticket_show_not_going":false,"_tribe_ticket_use_global_stock":"","_tribe_ticket_global_stock_level":"","_global_stock_mode":"","_global_stock_cap":"","_tribe_rsvp_for_event":"","_tribe_ticket_going_count":"","_tribe_ticket_not_going_count":"","_tribe_tickets_list":"[]","_tribe_ticket_has_attendee_info_fields":false},"news-category":[],"news-topic":[18],"organisation":[],"authorship":[],"acf":[],"yoast_head":"\nCombining sequencing approaches and omics to characterise microbiomes - LCSB - Universit\u00e9 du Luxembourg I Uni.lu<\/title>\n<meta name=\"description\" content=\"DNA contains the blueprint for life, be it for mammals, plants or microorganisms. 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A software is then used to reconstruct the original blueprint, i.e., to which genes the different DNA sequences contained in a sample correspond. This is called a metagenomic reconstruction. It allows researchers to\u00a0identify genes of interest and to understand the composition and functions of microbiomes. As technologies are fast evolving, scientists have now at their disposal different sequencing approaches and software to generate these metagenomic reconstructions. In an\u00a0article recently published in\u00a0Briefings in Bioinformatics, researchers of the Luxembourg Centre for Systems Biomedicine (LCSB) at the University of Luxembourg and from the Luxembourg Institute of Science and Technology (LIST) investigate how these different approaches impact the reconstruction and downstream analyses of microbiomes. They show that different sequencing technologies \u2013 long-read or short-read \u2013 as well as assembly strategies, meaning the choice of software used for the reconstruction of either long-read data, short-read data, or both in a hybrid approach, can lead to\u00a0different conclusions. This is especially relevant as the use of\u00a0emerging long-read sequencing\u00a0technologies\u00a0will increase in the future and discrepancies between approaches will need to be addressed. These findings pave the way for critical assessments of metagenomic reconstructions.","og_url":"https:\/\/www.uni.lu\/lcsb-fr\/news\/combining-sequencing-approaches-and-omics-to-characterise-microbiomes\/","og_site_name":"LCSB FR","og_image":[{"width":800,"height":600,"url":"https:\/\/www.uni.lu\/wp-content\/uploads\/sites\/22\/2021\/09\/combining_sequencing_approaches_and_omics_to_characterise_microbiomes.jpg","type":"image\/jpeg"}],"twitter_card":"summary_large_image","twitter_misc":{"Dur\u00e9e de lecture estim\u00e9e":"5 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"NewsArticle","@id":"https:\/\/www.uni.lu\/lcsb-fr\/news\/combining-sequencing-approaches-and-omics-to-characterise-microbiomes\/#article","isPartOf":{"@id":"https:\/\/www.uni.lu\/lcsb-fr\/news\/combining-sequencing-approaches-and-omics-to-characterise-microbiomes\/"},"author":{"name":"","@id":""},"headline":"Combining sequencing approaches and omics to characterise microbiomes","datePublished":"2021-09-01T13:39:39+00:00","dateModified":"2021-09-01T13:39:39+00:00","mainEntityOfPage":{"@id":"https:\/\/www.uni.lu\/lcsb-fr\/news\/combining-sequencing-approaches-and-omics-to-characterise-microbiomes\/"},"wordCount":978,"publisher":{"@id":"https:\/\/www.uni.lu\/lcsb-fr\/#organization"},"image":{"@id":"https:\/\/www.uni.lu\/lcsb-fr\/news\/combining-sequencing-approaches-and-omics-to-characterise-microbiomes\/#primaryimage"},"thumbnailUrl":"https:\/\/www.uni.lu\/wp-content\/uploads\/sites\/22\/2021\/09\/combining_sequencing_approaches_and_omics_to_characterise_microbiomes.jpg","inLanguage":"fr-FR"},{"@type":"WebPage","@id":"https:\/\/www.uni.lu\/lcsb-fr\/news\/combining-sequencing-approaches-and-omics-to-characterise-microbiomes\/","url":"https:\/\/www.uni.lu\/lcsb-fr\/news\/combining-sequencing-approaches-and-omics-to-characterise-microbiomes\/","name":"Combining sequencing approaches and omics to characterise microbiomes - LCSB - Universit\u00e9 du Luxembourg I Uni.lu","isPartOf":{"@id":"https:\/\/www.uni.lu\/lcsb-fr\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.uni.lu\/lcsb-fr\/news\/combining-sequencing-approaches-and-omics-to-characterise-microbiomes\/#primaryimage"},"image":{"@id":"https:\/\/www.uni.lu\/lcsb-fr\/news\/combining-sequencing-approaches-and-omics-to-characterise-microbiomes\/#primaryimage"},"thumbnailUrl":"https:\/\/www.uni.lu\/wp-content\/uploads\/sites\/22\/2021\/09\/combining_sequencing_approaches_and_omics_to_characterise_microbiomes.jpg","datePublished":"2021-09-01T13:39:39+00:00","dateModified":"2021-09-01T13:39:39+00:00","description":"DNA contains the blueprint for life, be it for mammals, plants or microorganisms. 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