Strategies and tools in illumina and nanopore-integrated metagenomic analysis of microbiome data

Characterizing the epidemiology of Mycoplasma pneumoniae infections in China in 2022-2024: a nationwide cross-sectional study of over 1.6 million cases

Mycoplasma pneumoniae (MP) is a leading cause of community-acquired pneumonia (CAP), accounting for 10-40% of cases in children. In China, the high prevalence of macrolide-resistant MP (MRMP) and recurrent MP epidemics place a significant burden on the healthcare system. Leveraging data from over 1.6 million cases, this study provides a comprehensive analysis of the epidemiological characteristics of MP across China. Seasonal patterns analysis revealed three distinct transmission zones in China. Transmission Zone 1 exhibited two annual epidemic peaks, while Zones 2 and 3 showed a single annual peak of distinct timings. Notably, winter travel to popular tourist destinations appears to influence MP infection patterns in China. Age- and sex- specific analysis indicated male newborns aged [0-1) years face a 1.67 times higher risk of MP infection compared to females. Conversely, females aged [23-38) years have a higher infection risk, likely due to their caregiving roles. The proportion of MRMP surged from 80.00% to 93.02% between July 2023 and May 2024, with a median growth rate of 10.21%. This rapid increase contrasts sharply with the modest 5.3% rise observed from 2011 to 2019, and we attribute this escalation in part to the growing prevalence of the T1-3R clade strain in China. These findings have important implications for the identification of high-risk population, place, and time for more targeted efforts of prevention and treatment. Furthermore, the rapidly increased proportion of MRMP in the 2023-2024 season raises a concerning signal regarding antibiotic use.

Nanopore Environmental Analysis

As global pollution continues to escalate, timely and accurate monitoring is essential for guiding pollution governance and safeguarding public health. The increasing diversity of pollutants across environmental matrices poses a significant challenge for instrumental analysis methods, which often require labor-intensive and time-consuming sample pretreatment. Nanopore technology, an emerging single-molecule technique, presents a promising solution by enabling the rapid identification of multiple targets within complex mixtures with minimal sample preparation. A wide range of pollutants have been characterized using natural biological nanopores or artificial solid-state nanopores, and their distinct advantages include simple sample preparation, high sensitivity, and rapid onsite analysis. In particular, long-read nanopore sequencing has led to dramatic improvements in the analyses of environmental microbial communities, allows species-level taxonomic assignment using amplicon sequencing, and simplifies the assembly of metagenomes. In this Perspective, we review the latest advancements in analyzing chemical and biological pollutants through nanopore sensing and sequencing techniques. We also explore the challenges that remain in this rapidly evolving field and provide an outlook on the potential for nanopore environmental analysis to transform pollution monitoring, risk assessment, and public health protection.

Advances in multi-omics integrated analysis methods based on the gut microbiome and their applications

The gut microbiota actually shares the host's physical space and affects the host's physiological functions and health indicators through a complex network of interactions with the host. However, its role as a determinant of host health and disease is often underestimated. With the emergence of new technologies including next-generation sequencing (NGS) and advanced techniques such as microbial community sequencing, people have begun to explore the interaction mechanisms between microorganisms and hosts at various omics levels such as genomics, transcriptomics, metabolomics, and proteomics. With the enrichment of multi-omics integrated analysis methods based on the microbiome, an increasing number of complex statistical analysis methods have also been proposed. In this review, we summarized the multi-omics research analysis methods currently used to study the interaction between the microbiome and the host. We analyzed the advantages and limitations of various methods and briefly introduced their application progress.

Sequencing Strategy to Ensure Accurate Plasmid Assembly

Despite the wide use of plasmids in research and clinical production, the need to verify plasmid sequences is a bottleneck that is too often underestimated in the manufacturing process. Although sequencing platforms continue to improve, the method and assembly pipeline chosen still influence the final plasmid assembly sequence. Furthermore, few dedicated tools exist for plasmid assembly, especially for de novo assembly. Here, we evaluated short-read, long-read, and hybrid (both short and long reads) de novo assembly pipelines across three replicates of a 24-plasmid library. Consistent with previous characterizations of each sequencing technology, short-read assemblies had issues resolving GC-rich regions, and long-read assemblies commonly had small insertions and deletions, especially in repetitive regions. The hybrid approach facilitated the most accurate, consistent assembly generation and identified mutations relative to the reference sequence. Although Sanger sequencing can be used to verify specific regions, some GC-rich and repetitive regions were difficult to resolve using any method, suggesting that easily sequenced genetic parts should be prioritized in the design of new genetic constructs.

MetaCONNET: A metagenomic polishing tool for long-read assemblies

Accurate and high coverage genome assemblies are the basis for downstream analysis of metagenomic studies. Long-read sequencing technology is an ideal tool to facilitate the assemblies of metagenome, except for the drawback of usually producing reads with high sequencing error rate. Many polishing tools were developed to correct the sequencing error, but most are designed on the ground of one or two species. Considering the complexity and uneven depth of metagenomic study, we present a novel deep-learning polishing tool named MetaCONNET for polishing metagenomic assemblies. We evaluate MetaCONNET against Medaka, CONNET and NextPolish in accuracy, coverage, contiguity and resource consumption. Our results demonstrate that MetaCONNET provides a valuable polishing tool and can be applied to many metagenomic studies.

Unlocking the Potential of Metagenomics with the PacBio High-Fidelity Sequencing Technology

Traditional methods for studying microbial communities have been limited due to difficulties in culturing and sequencing all microbial species. Recent advances in third-generation sequencing technologies, particularly PacBio's high-fidelity (HiFi) sequencing, have significantly advanced metagenomics by providing accurate long-read sequences. This review explores the role of HiFi sequencing in overcoming the limitations of previous sequencing methods, including high error rates and fragmented assemblies. We discuss the benefits and applications of HiFi sequencing across various environments, such as the human gut and soil, which provides broader context for further exploration. Key studies are discussed to highlight HiFi sequencing's ability to recover complete and coherent microbial genomes from complex microbiomes, showcasing its superior accuracy and continuity compared to other sequencing technologies. Additionally, we explore the potential applications of HiFi sequencing in quantitative microbial analysis, as well as the detection of single nucleotide variations (SNVs) and structural variations (SVs). PacBio HiFi sequencing is establishing a new benchmark in metagenomics, with the potential to significantly enhance our understanding of microbial ecology and drive forward advancements in both environmental and clinical applications.

Nanopore sequencing: flourishing in its teenage years

Over the past decade, nanopore sequencing has experienced significant advancements and changes, transitioning from an initially emerging technology to a significant instrument in the field of genomic sequencing. However, as advancements in next-generation sequencing technology persist, nanopore sequencing also improves. This paper reviews the developments, applications, and outlook on nanopore sequencing technology. Currently, nanopore sequencing supports both DNA and RNA sequencing, making it widely applicable in areas such as telomere-to-telomere (T2T) genome assembly, direct RNA sequencing (DRS), and metagenomics. The openness and versatility of nanopore sequencing have established it as a preferred option for an increasing number of research teams, signaling a transformative influence on life science research. As the nanopore sequencing technology advances, it provides a faster, more cost-effective approach with extended read lengths, demonstrating the significant potential for complex genome assembly, pathogen detection, environmental monitoring, and human disease research, offering a fresh perspective in sequencing technologies.

MetaAll: integrative bioinformatics workflow for analysing clinical metagenomic data

Over the past decade, there have been many improvements in the field of metagenomics, including sequencing technologies, advances in bioinformatics and the development of reference databases, but a one-size-fits-all sequencing and bioinformatics pipeline does not yet seem achievable. In this study, we address the bioinformatics part of the analysis by combining three methods into a three-step workflow that increases the sensitivity and specificity of clinical metagenomics and improves pathogen detection. The individual tools are combined into a user-friendly workflow suitable for analysing short paired-end (PE) and long reads from metagenomics datasets-MetaAll. To demonstrate the applicability of the developed workflow, four complicated clinical cases with different disease presentations and multiple samples collected from different biological sites as well as the CAMI Clinical pathogen detection challenge dataset were used. MetaAll was able to identify putative pathogens in all but one case. In this case, however, traditional microbiological diagnostics were also unsuccessful. In addition, co-infection with Haemophilus influenzae and Human rhinovirus C54 was detected in case 1 and co-infection with SARS-Cov-2 and Influenza A virus (FluA) subtype H3N2 was detected in case 3. In case 2, in which conventional diagnostics could not find a pathogen, mNGS pointed to Klebsiella pneumoniae as the suspected pathogen. Finally, this study demonstrated the importance of combining read classification, contig validation and targeted reference mapping for more reliable detection of infectious agents in clinical metagenome samples.

Sequencing Strategy to Ensure Accurate Plasmid Assembly

Despite the wide use of plasmids in research and clinical production, the need to verify plasmid sequences is a bottleneck that is too often underestimated in the manufacturing process. Although sequencing platforms continue to improve, the method and assembly pipeline chosen still influence the final plasmid assembly sequence. Furthermore, few dedicated tools exist for plasmid assembly, especially for de novo assembly. Here, we evaluated short-read, long-read, and hybrid (both short and long reads) de novo assembly pipelines across three replicates of a 24-plasmid library. Consistent with previous characterizations of each sequencing technology, short-read assemblies had issues resolving GC-rich regions, and long-read assemblies commonly had small insertions and deletions, especially in repetitive regions. The hybrid approach facilitated the most accurate, consistent assembly generation and identified mutations relative to the reference sequence. Although Sanger sequencing can be used to verify specific regions, some GC-rich and repetitive regions were difficult to resolve using any method, suggesting that easily sequenced genetic parts should be prioritized in the design of new genetic constructs.

Biosynthetic potential of uncultured anammox community bacteria revealed through multi-omics analysis

Microbial secondary metabolites (SMs) and their derivatives have been widely used in medicine, agriculture, and energy. Growing needs for renewable energy and the challenges posed by antibiotic resistance, cancer, and pesticides emphasize the crucial hunt for new SMs. Anaerobic ammonium-oxidation (anammox) systems harbor many uncultured or underexplored bacteria, representing potential resources for discovering novel SMs. Leveraging HiFi long-read metagenomic sequencing, 1,040 biosynthetic gene clusters (BGCs) were unearthed from the anammox microbiome with 58% being complete and showcasing rich diversity. Most of them showed distant relations to known BGCs, implying novelty. Members of the underexplored lineages (Chloroflexota and Planctomycetota) and Proteobacteria contained lots of BGCs, showcasing substantial biosynthetic potential. Metaproteomic results indicated that Planctomycetota members harbored the most active BGCs, particularly those involved in producing potential biofuel-ladderane. Overall, these findings underscore that anammox microbiomes could serve as valuable resources for mining novel BGCs and discovering new SMs for practical application.

Integrating multi-platform assembly to recover MAGs from hot spring biofilms: insights into microbial diversity, biofilm formation, and carbohydrate degradation

BACKGROUND

Hot spring biofilms provide a window into the survival strategies of microbial communities in extreme environments and offer potential for biotechnological applications. This study focused on green and brown biofilms thriving on submerged plant litter within the Sungai Klah hot spring in Malaysia, characterised by temperatures of 58-74 °C. Using Illumina shotgun metagenomics and Nanopore ligation sequencing, we investigated the microbial diversity and functional potential of metagenome-assembled genomes (MAGs) with specific focus on biofilm formation, heat stress response, and carbohydrate catabolism.

RESULTS

Leveraging the power of both Illumina short-reads and Nanopore long-reads, we employed an Illumina-Nanopore hybrid assembly approach to construct MAGs with enhanced quality. The dereplication process, facilitated by the dRep tool, validated the efficiency of the hybrid assembly, yielding MAGs that reflected the intricate microbial diversity of these extreme ecosystems. The comprehensive analysis of these MAGs uncovered intriguing insights into the survival strategies of thermophilic taxa in the hot spring biofilms. Moreover, we examined the plant litter degradation potential within the biofilms, shedding light on the participation of diverse microbial taxa in the breakdown of starch, cellulose, and hemicellulose. We highlight that Chloroflexota and Armatimonadota MAGs exhibited a wide array of glycosyl hydrolases targeting various carbohydrate substrates, underscoring their metabolic versatility in utilisation of carbohydrates at elevated temperatures.

CONCLUSIONS

This study advances understanding of microbial ecology on plant litter under elevated temperature by revealing the functional adaptation of MAGs from hot spring biofilms. In addition, our findings highlight potential for biotechnology application through identification of thermophilic lignocellulose-degrading enzymes. By demonstrating the efficiency of hybrid assembly utilising Illumina-Nanopore reads, we highlight the value of combining multiple sequencing methods for a more thorough exploration of complex microbial communities.

PlasCAT: Plasmid Cloud Assembly Tool

SUMMARY

PlasCAT (Plasmid Cloud Assembly Tool) is an easy-to-use cloud-based bioinformatics tool that enables de novo plasmid sequence assembly from raw sequencing data. Nontechnical users can now assemble sequences from long reads and short reads without ever touching a line of code. PlasCAT uses high-performance computing servers to reduce run times on assemblies and deliver results faster.

AVAILABILITY AND IMPLEMENTATION

PlasCAT is freely available on the web at https://sequencing.genofab.com. The assembly pipeline source code and server code are available for download at https://bitbucket.org/genofabinc/workspace/projects/PLASCAT. Click the Cancel button to access the source code without authenticating. Web servers implemented in React.js and Python, with all major browsers supported.

Correlation between the gut microbiome and neurodegenerative diseases: a review of metagenomics evidence

A growing body of evidence suggests that the gut microbiota contributes to the development of neurodegenerative diseases via the microbiota-gut-brain axis. As a contributing factor, microbiota dysbiosis always occurs in pathological changes of neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. High-throughput sequencing technology has helped to reveal that the bidirectional communication between the central nervous system and the enteric nervous system is facilitated by the microbiota's diverse microorganisms, and for both neuroimmune and neuroendocrine systems. Here, we summarize the bioinformatics analysis and wet-biology validation for the gut metagenomics in neurodegenerative diseases, with an emphasis on multi-omics studies and the gut virome. The pathogen-associated signaling biomarkers for identifying brain disorders and potential therapeutic targets are also elucidated. Finally, we discuss the role of diet, prebiotics, probiotics, postbiotics and exercise interventions in remodeling the microbiome and reducing the symptoms of neurodegenerative diseases.

ACR: metagenome-assembled prokaryotic and eukaryotic genome refinement tool

Microbial genome recovery from metagenomes can further explain microbial ecosystem structures, functions and dynamics. Thus, this study developed the Additional Clustering Refiner (ACR) to enhance high-purity prokaryotic and eukaryotic metagenome-assembled genome (MAGs) recovery. ACR refines low-quality MAGs by subjecting them to iterative k-means clustering predicated on contig abundance and increasing bin purity through validated universal marker genes. Synthetic and real-world metagenomic datasets, including short- and long-read sequences, evaluated ACR's effectiveness. The results demonstrated improved MAG purity and a significant increase in high- and medium-quality MAG recovery rates. In addition, ACR seamlessly integrates with various binning algorithms, augmenting their strengths without modifying core features. Furthermore, its multiple sequencing technology compatibilities expand its applicability. By efficiently recovering high-quality prokaryotic and eukaryotic genomes, ACR is a promising tool for deepening our understanding of microbial communities through genome-centric metagenomics.

The Skin Microbiome: Current Landscape and Future Opportunities

Our skin is the largest organ of the body, serving as an important barrier against the harsh extrinsic environment. Alongside preventing desiccation, chemical damage and hypothermia, this barrier protects the body from invading pathogens through a sophisticated innate immune response and co-adapted consortium of commensal microorganisms, collectively termed the microbiota. These microorganisms inhabit distinct biogeographical regions dictated by skin physiology. Thus, it follows that perturbations to normal skin homeostasis, as occurs with ageing, diabetes and skin disease, can cause microbial dysbiosis and increase infection risk. In this review, we discuss emerging concepts in skin microbiome research, highlighting pertinent links between skin ageing, the microbiome and cutaneous repair. Moreover, we address gaps in current knowledge and highlight key areas requiring further exploration. Future advances in this field could revolutionise the way we treat microbial dysbiosis associated with skin ageing and other pathologies.