Benchmarking second and third-generation sequencing platforms for microbial metagenomics

Positive nutritional selection of adults with healthy lifestyle and high daily fiber consumption for the isolation of beneficial intestinal bacteria: The iTARGET cohort study protocol

Recent advances in the study of the gut microbiota has pointed to its under-utilized source of potentially beneficial bacteria, known as next generation probiotics, offering a promising avenue to restore or compensate impaired gut microbiota toward a healthy state. Aside from the difficulties to achieve in-lab adequate culture conditions, the use of beneficial bacterial isolates is also limited by their bioavailability in the donor itself. In the iTARGET study, we positively selected donors based on their diet enriched in fiber, that has been shown to increase the prevalence of bacterial species associated with health. The iTARGET study is a monocenter, prospective, observational study of adults with healthy lifestyle and high daily fiber consumption. We aim to recruit individuals in two phases, the first one for all individuals that will permit the identification of carriers for bacteria of interest and the second phase for a subset of individuals to allow for culture and isolation of previously identified potentially beneficial bacteria. Our primary outcome is the isolation and culture of at least one potentially beneficial isolate. The secondary outcomes comprised the high throughput metagenomic profiles of the intestinal microbiota and the characterization of the cultured isolates. The study was approved by the French Research Ethics Committees (Comité de Protection des Personnes Sud-Est I) under the National reference ID 2023-A01677-38. Study findings and results will be published in peer-reviewed Open Access journals. (Trial registration number on ClinicalTrials.gov: NCT06166810).

Clinical value of Metagenomic Next- and Third-Generation Sequencing applied in ultrasound-guided puncture biopsy for diagnosing lymph node tuberculosis

OBJECTIVES

The aim of this study was to assess the clinical utility of metagenomic next-generation sequencing (mNGS) and metagenomic third-generation sequencing (mTGS) in diagnosing cervical lymph node tuberculosis through analysis of lymph node tissue.

METHODS

This study recruited 101 patients with suspected cervical lymph node tuberculosis and took samples under ultrasound guidance. Parallel culture, X-pert, mNGS and mTGS workflows to each sample were performed. Taking clinical diagnosis as the gold standard, We comparatively compared diagnosis performance of the four methods.

RESULTS

Clinically, 76 cases were diagnosed as lymph node tuberculosis and 20 cases were non-lymph node tuberculosis. Compared with clinical diagnosis, the sensitivities of mNGS and mTGS were 89.47 % and 82.89 %, respectively, significantly higher than those of culture and X-pert which were 43.28 % and 68.42 %, respectively (P < 0.05). The specificity of mNGS and X-pert reached 100 %, while those of culture and mTGS were 93.75 % and 95 %, respectively. And mNGS alone identified 7 species of bacteria, 3 species of viruses, and 5 species of fungi, and identified more mixed infections. Particularly, besides Mycobacterium tuberculosis detection, mNGS may be superior to mTGS for the detection of fungi. Pathogen identification of mNGS and mTGS is less affected by previous anti-tuberculosis drug usage.

CONCLUSION

mNGS and mTGS play a crucial role in the rapid diagnosis and accurate treatment on Cervical lymph node tuberculosis.

Comprehensive genome analysis of two Cytospora (Cytosporaceae, Diaporthales) species associated with canker disease of spruce: C.piceae and C.piceicola sp. nov

Cytospora canker (CC) is among the most important diseases in conifer trees (Picea spp., mainly). This disease poses a significant risk factor for forest health, potentially leading to economic losses for wood producers. To provide a genomic basis of the CC pathogenesis, the genomes of two Cytospora species associated with the disease were sequenced and further analyzed within a set of Diaporthales species. The first species was identified as C.piceae. The second was described as C.piceicola sp. nov. based on morphological characteristics and multi-gene phylogenetic analysis. The novel species is sister to other Cytospora species isolated from conifers. Here, we report 39.7 and 43.8 Mb highly contiguous genome assemblies of C.piceae EI-19(A) and C.piceicola EI-20, respectively, obtained using Illumina sequencing technology. Despite notably different genome sizes, these species share the main genome characteristics, such as predicted gene number (10,862 and 10,742) and assembly completeness (97.6% and 98.1%). A wide range of genes encoding carbohydrate-active enzymes, secondary metabolite biosynthesis clusters, and secreted effectors were found. Multiple experimentally validated virulence genes were also identified in the studied species. The defined arsenals of enzymes and effectors generally relate to the hemibiotrophic lifestyle with a capability to switch to biotrophy. The obtained evidence also supports that C.piceae EI-19(A) and C.piceicola EI-20 can cause severe canker disease symptoms in Picea spp. specifically. It was additionally observed that the strains of C.piceae may have different pathogenicity and virulence characteristics based on the analyses of predicted secondary metabolite complements, effectomes, and virulence-related genes. Phylogenomic analysis and timetree estimations indicated that divergence of the studied species may have occurred relatively late, 11-10 million years ago. Compared to other members of Diaporthales, C.piceae EI-19(A) and C.piceicola EI-20 implied a moderate rate of gene contraction, but the latter experienced significant gene loss that can additionally support host specificity attributed to these species. But uncovered gene contraction events may point out potential lifestyle differentiation and host shift of the studied species. It was revealed that EI-19(A) and C.piceicola EI-20 carry distinct secretomes and effectomes among Diaporthales species. This feature can indicate a species lifestyle and pathogenicity potential. These findings highlight potential targets for identification and/or detection of pathogenic Cytospora in conifers. The introduced draft genome sequences of C.piceae and C.piceicola can be employed as tools to understand basic genetics and pathogenicity mechanisms of fungal species causing canker disease in woody plants. The identified pathogenicity and virulence-related genes would serve as potential candidates for host-induced gene silencing aimed at making plant hosts more resistant to pathogenic species. Furthermore, the comparative genomics component of the study will facilitate the functional analysis of the genes of unknown function in all fungal pathogens.

Short-Read and Long-Read Whole Genome Sequencing for SARS-CoV-2 Variants Identification

Genomic surveillance of SARS-CoV-2 is crucial for detecting emerging variants and informing public health responses. Various sequencing technologies are used for whole genome sequencing of SARS-CoV-2. This cross-platform benchmark study applied established bioinformatics tools to assess and improve the performance of Illumina NovaSeq, Oxford Nanopore Technologies MinION, and Pacific Biosciences Sequel II sequencing platforms in identifying SARS-CoV-2 variants and lineage assignment. NovaSeq produced the highest number of reads and bases, depth of coverage, completeness of consensus genomes, stable mapping coverage across open reading frames in the genome, and consistent lineage assignments. The long-read sequencing platforms had lower yields, sequencing depth, and mapping coverage, limiting the number of qualified sequences for lineage assignment and variant identification. However, implementing proper quality controls on sequence data overcame these limitations and achieved consistent SARS-CoV-2 lineage assignments across all three sequencing platforms. The advancements in library preparation and technology for long-read sequencing are likely to enhance sequence quality and expand genome coverage, effectively addressing current limitations in genome analysis. By merging the unique advantages of both short- and long-read methods, we can significantly improve SARS-CoV-2 genomic surveillance and provide insights into sequencing strategies for other RNA viruses, pending further validation. This may lead to precise tracking of viral evolution and support public health policy decisions.

Long-read metagenomics gives a more accurate insight into the microbiota of long-ripened gouda cheeses

Metagenomic studies of the Gouda cheese microbiota and starter cultures are scarce. During the present study, short-read metagenomic sequencing (Illumina) was applied on 89 Gouda cheese and processed milk samples, which have been investigated before concerning their metabolite and taxonomic composition, the latter applying amplicon-based, high-throughput sequencing (HTS) of the full-length 16S rRNA gene. Selected samples were additionally investigated using long-read metagenomic sequencing (Oxford Nanopore Technologies, ONT). Whereas the species identified by amplicon-based HTS and metagenomic sequencing were identical, the relative abundances of the major species differed significantly. Lactococcus cremoris was more abundant in the metagenomics-based taxonomic analysis compared to the amplicon-based one, whereas the opposite was true for the non-starter lactic acid bacteria (NSLAB). This discrepancy was related to a higher fragmentation of the lactococcal DNA compared with the DNA of other species when applying ONT. Possibly, a higher fragmentation was linked with a higher percentage of dead or metabolically inactive cells, suggesting that full-length 16S rRNA gene amplicon-based HTS might give a more accurate view on active cells. Further, fungi were not abundantly present in the Gouda cheeses examined, whereas about 2% of the metagenomic sequence reads was related to phages, with higher relative abundances in the cheese rinds and long-ripened cheeses. Intraspecies differences found by short-read metagenomic sequencing were in agreement with the amplicon sequence variants obtained previously, confirming the ability of full-length 16S rRNA gene amplicon-based HTS to reach a taxonomic assignment below species level. Metagenome-assembled genomes (MAGs) were retrieved for 15 species, among which the starter cultures Lc. cremoris and Lactococcus lactis and the NSLAB Lacticaseibacillus paracasei, Loigolactobacillus rennini, and Tetragenococcus halophilus, although obtaining MAGs from Lc. cremoris and Lc. lactis was more challenging because of a high intraspecies diversity and high similarity between these species. Long-read metagenomic sequencing could not improve the retrieval of lactococcal MAGs, but, overall, MAGs obtained by long-read metagenomic sequencing solely were superior compared with those obtained by short-read metagenomic sequencing solely, reaching a high-quality draft status of the genomes.

Development of a quantitative metagenomic approach to establish quantitative limits and its application to viruses

Quantitative metagenomic methods are maturing but continue to lack clearly-defined analytical limits. Here, we developed a computational tool, QuantMeta, to determine the absolute abundance of targets in metagenomes spiked with synthetic DNA standards. The tool establishes (i) entropy-based detection thresholds to confidently determine the presence of targets, and (ii) an approach to identify and correct read mapping or assembly errors and thus improve the quantification accuracy. Together this allows for an approach to confidently quantify absolute abundance of targets, be they microbial populations, genes, contigs, or metagenome-assembled genomes. We applied the approach to quantify single- and double-stranded DNA viruses in wastewater viral metagenomes, including pathogens and bacteriophages. Concentrations of total DNA viruses in wastewater influent and effluent were >108 copies/ml using QuantMeta. Human-associated DNA viruses were detected and quantifiable with QuantMeta thresholds, including polyomavirus, papillomavirus, and crAss-like phages, at concentrations similar to previous reports that utilized quantitative polymerase chain reaction (PCR)-based assays. Our results highlight the higher detection thresholds of quantitative metagenomics (approximately 500 copies/μl) as compared to PCR-based quantification (approximately 10 copies/μl) despite a sequencing depth of 200 million reads per sample. The QuantMeta approach, applicable to both viral and cellular metagenomes, advances quantitative metagenomics by improving the accuracy of measured target absolute abundances.

Diagnostic value of nanopore sequencing of cerebrospinal fluid samples in tuberculous meningitis

OBJECTIVE

To investigate the diagnostic efficacy of nanopore sequencing technology in tuberculous meningitis (TBM).

METHODS

Cerebrospinal fluid samples were collected from patients for acid-fast staining microscopy, Mycobacterium tuberculosis solid culture, DNA detection, and nanopore sequencing. Lastly, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the receiver operating characteristic curve (AUC) were calculated and compared among these detection methods.

RESULTS

In this study, 30 TBM patients and 18 non-TBM patients were included. Nanopore sequencing showed higher sensitivity (43.30 %) and AUC (0.661) compared to the other methods. Combining nanopore sequencing and imaging achieved the highest diagnostic performance with sensitivity (60.00 %), specificity (88.90 %), PPV (90.00 %), NPV (57.10 %), and AUC (0.744).

CONCLUSION

Nanopore sequencing demonstrated superior diagnostic accuracy for TBM, outperforming acid-fast staining, Mycobacterium tuberculosis culture, and DNA detection. When combined with imaging, nanopore sequencing significantly enhanced diagnostic sensitivity and accuracy for TBM.

Diagnostic value of third-generation nanopore sequencing in extrapulmonary tuberculosis

Background

This study aimed to explore the accuracy of third-generation nanopore sequencing to diagnose extrapulmonary tuberculosis (EPTB).

Methods

Samples were collected from the lesions of 67 patients with suspected EPTB admitted between April 2022 and August 2023. Nanopore sequencing, acid-fast bacilli (AFB) staining, DNA testing, and X-pert and mycobacterial cultures were performed. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and area under the receiver operating characteristic curve (AUC) were calculated for different diagnostic methods, and their diagnostic accuracies were compared.

Results

Nanopore sequencing demonstrated the highest correct diagnosis rate among 50 positive EPTB cases, independently diagnosing 19 positive cases missed by conventional methods. Its sensitivity (62.00%), specificity (94.10%), PPV (96.90%), NPV (45.70%) and AUC (0.781, 95% CI: 0.67-0.89) were superior to those of conventional methods, such as AFB staining, DNA testing, X-pert, and solid culture, indicating its significantly efficient advantage in EPTB detection.

Conclusion

Nanopore sequencing technology significantly outperforms conventional methods such as AFB staining, DNA testing, X-pert, and mycobacterial culture to diagnose EPTB, promising to improve the diagnosis of EPTB.

Diabetes and gut microbiome

Diabetes mellitus represents a significant global health problem. The number of people suffering from this metabolic disease is constantly rising and although the incidence is heterogeneous depending on region, country, economic situation, lifestyle, diet and level of medical care, it is increasing worldwide, especially among youths and children, mainly due to lifestyle and environmental changes. The pathogenesis of the two most common subtypes of diabetes mellitus, type 1 (T1DM) and type 2 (T2DM), is substantially different, so each form is characterized by a different causation, etiology, pathophysiology, presentation, and treatment. Research in recent decades increasingly indicates the potential role of the gut microbiome in the initiation, development, and progression of this disease. Intestinal microbes and their fermentation products have an important impact on host metabolism, immune system, nutrient digestion and absorption, gut barrier integrity and protection against pathogens. This review summarizes the current evidence on the changes in gut microbial populations in both types of diabetes mellitus. Attention is focused on changes in the abundance of specific bacterial groups at different taxonomic levels in humans, and microbiome shift is also assessed in relation to geographic location, age, diet and antidiabetic drug. The causal relationship between gut bacteria and diabetes is still unclear, and future studies applying new methodological approaches to a broader range of microorganisms inhabiting the digestive tract are urgently needed. This would not only provide a better understanding of the role of the gut microbiome in this metabolic disease, but also the use of beneficial bacterial species in the form of probiotics for the treatment of diabetes.

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.

Bacterial and fungal aerosols in poultry houses: PM2.5 metagenomics via single-molecule real-time sequencing

Microbial aerosol contamination is a common problem in poultry farms, posing potential health risks to poultry and their caretakers. Exploring the distribution and diversity of the microbial community in poultry farm aerosols is crucial for effective mitigation strategies. The composition of bacterial and fungal aerosols is poorly understood, particularly the prevalence of potential pathogenic microorganisms in fine particulate matter (PM2.5) in various types of poultry houses. In this study, 27 PM2.5 samples were collected from 5 chicken houses and 4 duck houses in Shandong Province, China. Species-level diversity of bacterial and fungal components in PM2.5 samples was determined using advanced single-molecule real-time sequencing (SMRT) technology, based on the 16S and internal transcribed spacer 1 (ITS) ribosomal genes. Microbial diversity and community composition varied significantly across the different poultry house. Notably, duck houses had higher concentrations (p < 0.01) of PM2.5 (92.8-143.1 μg/m3) than chicken houses (42.0-56.4 μg/m3). Furthermore, microbial variation in PM2.5 samples was associated with the type of poultry facility. The predominant pathogenic microorganisms included Aspergillus sydowii, Penicillium sp., Aspergillus insolitus, Cladosporium sp., Aspergillus sp., Aspergillus pseudoglaucus, Cladosporium sp. C4092-2-PD1, and Colletotrichum sp., all of which were classified as second category of pathogens. Aspergillus sydowii and Penicillium sp. were the dominant species in chicken houses, while Cladosporium sp., Aspergillus sp., and Aspergillus pseudoglaucus were the dominant species identified in duck houses. To our knowledge, this study is the first to investigate bacterial and fungal diversity in PM2.5 samples collected from various types of poultry houses. These findings advance our understanding of poultry environmental microbiology and have important implications for safeguarding the health of both poultry and their caretakers.

Simple, reference-independent assessment to empirically guide correction and polishing of hybrid microbial community metagenomic assembly

Hybrid metagenomic assembly of microbial communities, leveraging both long- and short-read sequencing technologies, is becoming an increasingly accessible approach, yet its widespread application faces several challenges. High-quality references may not be available for assembly accuracy comparisons common for benchmarking, and certain aspects of hybrid assembly may benefit from dataset-dependent, empiric guidance rather than the application of a uniform approach. In this study, several simple, reference-free characteristics-particularly coding gene content and read recruitment profiles-were hypothesized to be reliable indicators of assembly quality improvement during iterative error-fixing processes. These characteristics were compared to reference-dependent genome- and gene-centric analyses common for microbial community metagenomic studies. Two laboratory-scale bioreactors were sequenced with short- and long-read platforms, and assembled with commonly used software packages. Following long read assembly, long read correction and short read polishing were iterated up to ten times to resolve errors. These iterative processes were shown to have a substantial effect on gene- and genome-centric community compositions. Simple, reference-free assembly characteristics, specifically changes in gene fragmentation and short read recruitment, were robustly correlated with advanced analyses common in published comparative studies, and therefore are suitable proxies for hybrid metagenome assembly quality to simplify the identification of the optimal number of correction and polishing iterations. As hybrid metagenomic sequencing approaches will likely remain relevant due to the low added cost of short-read sequencing for differential coverage binning or the ability to access lower abundance community members, it is imperative that users are equipped to estimate assembly quality prior to downstream analyses.

Comprehensive retrospect and future perspective on bacteriophage and cancer

BACKGROUND

Researchers gradually focus on the relationship between phage and cancer.

OBJECTIVE

To summarize the research hotspots and trends in the field of bacteriophage and cancer.

METHODS

The downloaded articles were searched from the Web of Science Core Collection database from January 2008 to June 2023. Bibliometric analysis was carried out through CiteSpace, including the analysis of cooperative networks (country/region, institution, and author), co-citations of references, and key words.Visual analysis of three topics, including gut phage, phage and bacteria, and phage and tumor, was conducted.

RESULTS

Overall, the United States and China have the most phage-related research. In terms of gut phage, the future research directions are "gut microbiome", "database" and "microbiota". The bursting citations explored the phage-dominated viral genome to discover its diversity and individual specificity and investigated associations among bacteriome, metabolome, and virome. In terms of phage and bacteria, "lipopolysaccharide" and "microbiota" are future research directions. Future research hotspots should mainly concentrate on the further exploration and application of phage properties. As for phages and tumors, the future research directions should be "colorectal cancer", "protein" and "phage therapy". Future directions are likely to focus on the research on phages in cancer mechanisms, cancer diagnosis, and cancer treatment combined with genetic engineering techniques.

CONCLUSION

Phage therapy would become a hot spot and research direction of tumor and phage research, and the relationship between phage and tumor, especially colorectal cancer (CRC), is expected to be further explored.

TRP channels in cancer: Therapeutic opportunities and research strategies

The influence of gut microbiota on transient receptor potential (TRP) channels has been identified as an important element in the development of gastrointestinal conditions, yet its involvement in cancer progression is not as thoroughly understood. This review explores the multifaceted roles of TRP channels in oncogenesis and emphasizes their significance in cancer progression and therapeutic outcomes. Critical focus was placed on the influence of traditional medicines, such as traditional Chinese medicine (TCM) related aromatic medicines, on TRP channel functions. Moreover, we explored the interplay between the gut microbiota and TRP channels in cancer signaling, highlighting the therapeutic potential of targeting this axis in cancer treatment. The impact of current therapies on TRP channel function was examined, demonstrating the need for a comprehensive understanding of how different modalities affect TRP channels in cancer. Technological advancements, including artificial intelligence (AI) tools and computer-aided drug development (CADD), have been discussed in the context of leveraging TRP channels for innovative cancer therapies. Future directions emphasize the potential applications of TRP channel research in advancing cancer treatment and enhancing patients' well-being.

Chromosome-level genome assembly and functional annotation of Citrullus colocynthis: unlocking genetic resources for drought-resilient crop development

MAIN CONCLUSION

The chromosome-level genome assembly of Citrullus colocynthis reveals its genetic potential for enhancing drought tolerance, paving the way for innovative crop improvement strategies. This study presents the first comprehensive genome assembly and annotation of Citrullus colocynthis, a drought-tolerant wild close relative of cultivated watermelon, highlighting its potential for enhancing agricultural resilience to climate change. The study achieved a chromosome-level assembly using advanced sequencing technologies, including PacBio HiFi and Hi-C, revealing a genome size of approximately 366 Mb with low heterozygosity and substantial repetitive content. Our analysis identified 23,327 gene models, that could encode stress response mechanisms for species' adaptation to arid environments. Comparative genomics with closely related species illuminated the evolutionary dynamics within the Cucurbitaceae family. In addition, resequencing of 27 accessions from the United Arab Emirates (UAE) identified genetic diversity, suggesting a foundation for future breeding programs. This genomic resource opens new avenues for the de novo domestication of C. colocynthis, offering a blueprint for developing crops with enhanced drought tolerance, disease resistance, and nutritional profiles, crucial for sustaining future food security in the face of escalating climate challenges.

Rapid species-level metagenome profiling and containment estimation with sylph

Profiling metagenomes against databases allows for the detection and quantification of microorganisms, even at low abundances where assembly is not possible. We introduce sylph, a species-level metagenome profiler that estimates genome-to-metagenome containment average nucleotide identity (ANI) through zero-inflated Poisson k-mer statistics, enabling ANI-based taxa detection. On the Critical Assessment of Metagenome Interpretation II (CAMI2) Marine dataset, sylph was the most accurate profiling method of seven tested. For multisample profiling, sylph took >10-fold less central processing unit time compared to Kraken2 and used 30-fold less memory. Sylph's ANI estimates provided an orthogonal signal to abundance, allowing for an ANI-based metagenome-wide association study for Parkinson disease (PD) against 289,232 genomes while confirming known butyrate-PD associations at the strain level. Sylph took <1 min and 16 GB of random-access memory to profile metagenomes against 85,205 prokaryotic and 2,917,516 viral genomes, detecting 30-fold more viral sequences in the human gut compared to RefSeq. Sylph offers precise, efficient profiling with accurate containment ANI estimation even for low-coverage genomes.

Imputing Metagenomic Hi-C Contacts Facilitates the Integrative Contig Binning Through Constrained Random Walk with Restart

Metagenomic Hi-C (metaHi-C) has shown remarkable potential for retrieving high-quality metagenome-assembled genomes from complex microbial communities. Nevertheless, existing metaHi-C-based contig binning methods solely rely on Hi-C interactions between contigs, disregarding crucial biological information such as the presence of single-copy marker genes. To overcome this limitation, we introduce ImputeCC, an integrative contig binning tool optimized for metaHi-C datasets. ImputeCC integrates both Hi-C interactions and the discriminative power of single-copy marker genes to group marker-gene-containing contigs into preliminary bins. It also introduces a novel constrained random walk with restart algorithm to enhance Hi-C connectivity among contigs. Comprehensive assessments using both mock and real metaHi-C datasets from diverse environments demonstrate that ImputeCC consistently outperforms other Hi-C-based contig binning tools. A genus-level analysis of the sheep gut microbiota reconstructed by ImputeCC underlines its capability to recover key species from dominant genera and identify previously unknown genera.

Efficient and easy-to-use capturing three-dimensional metagenome interactions with GutHi-C

Hi-C can obtain three-dimensional chromatin structure information and is widely used for genome assembly. We constructed the GutHi-C technology. As shown in the graphical abstract, it is a highly efficient and quick-to-operate method and can be widely used for human, livestock, and poultry gut microorganisms. It provides a reference for the Hi-C methodology of the microbial metagenome. DPBS, Dulbecco's phosphate-buffered saline; Hi-C, high-through chromatin conformation capture; LB, Luria-Bertani; NGS, next-generation sequencing; PCR, polymerase chain reaction; QC, quality control.

Crossing epigenetic frontiers: the intersection of novel histone modifications and diseases

Histone post-translational modifications (HPTMs), as one of the core mechanisms of epigenetic regulation, are garnering increasing attention due to their close association with the onset and progression of diseases and their potential as targeted therapeutic agents. Advances in high-throughput molecular tools and the abundance of bioinformatics data have led to the discovery of novel HPTMs which similarly affect gene expression, metabolism, and chromatin structure. Furthermore, a growing body of research has demonstrated that novel histone modifications also play crucial roles in the development and progression of various diseases, including various cancers, cardiovascular diseases, infectious diseases, psychiatric disorders, and reproductive system diseases. This review defines nine novel histone modifications: lactylation, citrullination, crotonylation, succinylation, SUMOylation, propionylation, butyrylation, 2-hydroxyisobutyrylation, and 2-hydroxybutyrylation. It comprehensively introduces the modification processes of these nine novel HPTMs, their roles in transcription, replication, DNA repair and recombination, metabolism, and chromatin structure, as well as their involvement in promoting the occurrence and development of various diseases and their clinical applications as therapeutic targets and potential biomarkers. Moreover, this review provides a detailed overview of novel HPTM inhibitors targeting various targets and their emerging strategies in the treatment of multiple diseases while offering insights into their future development prospects and challenges. Additionally, we briefly introduce novel epigenetic research techniques and their applications in the field of novel HPTM research.

Evaluating metagenomics and targeted approaches for diagnosis and surveillance of viruses

BACKGROUND

Metagenomics is a powerful approach for the detection of unknown and novel pathogens. Workflows based on Illumina short-read sequencing are becoming established in diagnostic laboratories. However, high sequencing depth requirements, long turnaround times, and limited sensitivity hinder broader adoption. We investigated whether we could overcome these limitations using protocols based on untargeted sequencing with Oxford Nanopore Technologies (ONT), which offers real-time data acquisition and analysis, or a targeted panel approach, which allows the selective sequencing of known pathogens and could improve sensitivity.

METHODS

We evaluated detection of viruses with readily available untargeted metagenomic workflows using Illumina and ONT, and an Illumina-based enrichment approach using the Twist Bioscience Comprehensive Viral Research Panel (CVRP), which targets 3153 viruses. We tested samples consisting of a dilution series of a six-virus mock community in a human DNA/RNA background, designed to resemble clinical specimens with low microbial abundance and high host content. Protocols were designed to retain the host transcriptome, since this could help confirm the absence of infectious agents. We further compared the performance of commonly used taxonomic classifiers.

RESULTS

Capture with the Twist CVRP increased sensitivity by at least 10-100-fold over untargeted sequencing, making it suitable for the detection of low viral loads (60 genome copies per ml (gc/ml)), but additional methods may be needed in a diagnostic setting to detect untargeted organisms. While untargeted ONT had good sensitivity at high viral loads (60,000 gc/ml), at lower viral loads (600-6000 gc/ml), longer and more costly sequencing runs would be required to achieve sensitivities comparable to the untargeted Illumina protocol. Untargeted ONT provided better specificity than untargeted Illumina sequencing. However, the application of robust thresholds standardized results between taxonomic classifiers. Host gene expression analysis is optimal with untargeted Illumina sequencing but possible with both the CVRP and ONT.

CONCLUSIONS

Metagenomics has the potential to become standard-of-care in diagnostics and is a powerful tool for the discovery of emerging pathogens. Untargeted Illumina and ONT metagenomics and capture with the Twist CVRP have different advantages with respect to sensitivity, specificity, turnaround time and cost, and the optimal method will depend on the clinical context.

Molecular characterization and transcriptional response of Lactuca sativa seedlings to co-exposure to graphene nanoplatelets and titanium dioxide nanoparticles

The widespread use of nanomaterials in agriculture may introduce multiple engineered nanoparticles (ENPs) into the environment, posing a combined risk to crops. However, the precise molecular mechanisms explaining how plant tissues respond to mixtures of individual ENPs remain unclear, despite indications that their combined toxicity differs from the summed toxicity of the individual ENPs. Here, we used a variety of methods including physicochemical, biochemical, and transcriptional analyses to examine the combined effects of graphene nanoplatelets (GNPs) and titanium dioxide nanoparticles (TiO2 NPs) on hydroponically exposed lettuce (Lactuca sativa) seedlings. Results indicated that the presence of GNPs facilitated the accumulation of Ti as TiO2 NPs in the seedling roots. Combined exposure to GNPs and TiO2 NPs caused less severe oxidative damage in the roots compared to individual exposures. Yet, GNPs and TiO2 NPs alone and in combination did not cause oxidative damage in the shoots. RNA sequencing data showed that the mixture of GNPs and TiO2 NPs led to a higher number of differentially expressed genes (DEGs) in the seedlings compared to exposure to the individual ENPs. Moreover, the majority of the DEGs encoding superoxide dismutase displayed heightened expression levels in the seedlings exposed to the combination of GNPs and TiO2 NPs. The level of gene ontology (GO) enrichment in the seedlings exposed to the mixture of GNPs and TiO2 NPs was found to be greater than the level of GO enrichment observed after exposure to isolated GNPs or TiO2 NPs. Furthermore, the signaling pathways, specifically the "MAPK signaling pathway-plant" and "phenylpropanoid biosynthesis," exhibited a close association with oxidative stress. This study has provided valuable insights into the molecular mechanisms underlying plant resistance against multiple ENPs.

New methods to detect bacterial or viral infections in patients with chronic obstructive pulmonary disease

INTRODUCTION

Patients with chronic obstructive pulmonary disease (COPD) are frequently colonized and infected by respiratory pathogens. Identifying these infectious etiologies is critical for understanding the microbial dynamics of COPD and for the appropriate use of antimicrobials during exacerbations.

AREAS COVERED

Traditional methods, such as bacterial and viral cultures, have been standard in diagnosing respiratory infections. However, these methods have significant limitations, including lack of sensitivity and prolonged turnaround time. Modern molecular approaches offer rapid, sensitive, and specific detection, though they also come with their own challenges. This review explores and evaluates the clinical utility of the latest advancements in detecting bacterial and viral respiratory infections in COPD, encompassing molecular techniques, biomarkers, and emerging technologies.

EXPERT OPINION

In the evolving landscape of COPD management, integrating molecular diagnostics and emerging technologies holds great promise. The enhanced sensitivity of molecular techniques has significantly advanced our understanding of the role of microbes in COPD. However, many of these technologies have primarily been developed for pneumonia diagnosis or research applications, and their clinical utility in managing COPD requires further evaluation.

Benchmarking bacterial taxonomic classification using nanopore metagenomics data of several mock communities

Taxonomic classification is crucial in identifying organisms within diverse microbial communities when using metagenomics shotgun sequencing. While second-generation Illumina sequencing still dominates, third-generation nanopore sequencing promises improved classification through longer reads. However, extensive benchmarking studies on nanopore data are lacking. We systematically evaluated performance of bacterial taxonomic classification for metagenomics nanopore sequencing data for several commonly used classifiers, using standardized reference sequence databases, on the largest collection of publicly available data for defined mock communities thus far (nine samples), representing different research domains and application scopes. Our results categorize classifiers into three categories: low precision/high recall; medium precision/medium recall, and high precision/medium recall. Most fall into the first group, although precision can be improved without excessively penalizing recall with suitable abundance filtering. No definitive 'best' classifier emerges, and classifier selection depends on application scope and practical requirements. Although few classifiers designed for long reads exist, they generally exhibit better performance. Our comprehensive benchmarking provides concrete recommendations, supported by publicly available code for reassessment and fine-tuning by other scientists.

Unveiling errors in soil microbial community sequencing: a case for reference soils and improved diagnostics for nanopore sequencing

The sequencing platform and workflow strongly influence microbial community analyses through potential errors at each step. Effective diagnostics and experimental controls are needed to validate data and improve reproducibility. This cross-laboratory study evaluates sources of variability and error at three main steps of a standardized amplicon sequencing workflow (DNA extraction, polymerase chain reaction [PCR], and sequencing) using Oxford Nanopore MinION to analyze agricultural soils and a simple mock community. Variability in sequence results occurs at each step in the workflow with PCR errors and differences in library size greatly influencing diversity estimates. Common bioinformatic diagnostics and the mock community are ineffective at detecting PCR abnormalities. This work outlines several diagnostic checks and techniques to account for sequencing depth and ensure accuracy and reproducibility in soil community analyses. These diagnostics and the inclusion of a reference soil can help ensure data validity and facilitate the comparison of multiple sequencing runs within and between laboratories.

Phylogenetic incongruence in an Asiatic species complex of the genus Caryodaphnopsis (Lauraceae)

BACKGROUND

Caryodaphnopsis, a group of tropical trees (ca. 20 spp.) in the family Lauraceae, has an amphi-Pacific disjunct distribution: ten species are distributed in Southeast Asia, while eight species are restricted to tropical rainforests in South America. Previously, phylogenetic analyses using two nuclear markers resolved the relationships among the five species from Latin America. However, the phylogenetic relationships between the species in Asia remain poorly known.

RESULTS

Here, we first determined the complete mitochondrial genome (mitogenome), plastome, and the nuclear ribosomal cistron (nrDNA) sequences of C. henryi with lengths of 1,168,029 bp, 154,938 bp, and 6495 bp, respectively. We found 2233 repeats and 368 potential SSRs in the mitogenome of C. henryi and 50 homologous DNA fragments between its mitogenome and plastome. Gene synteny analysis revealed a mass of rearrangements in the mitogenomes of Magnolia biondii, Hernandia nymphaeifolia, and C. henryi and only six conserved clustered genes among them. In order to reconstruct relationships for the ten Caryodaphnopsis species in Asia, we created three datasets: one for the mitogenome (coding genes and ten intergenic regions), another for the plastome (whole genome), and the other for the nuclear ribosomal cistron. All of the 22 Caryodaphnopsis individuals were divided into four, five, and six different clades in the phylogenies based on mitogenome, plastome, and nrDNA datasets, respectively.

CONCLUSIONS

The study showed phylogenetic conflicts within and between nuclear and organellar genome data of Caryodaphnopsis species. The sympatric Caryodaphnopsis species in Hekou and Malipo SW China may be related to the incomplete lineage sorting, chloroplast capture, and/or hybridization, which mixed the species as a complex in their evolutionary history.

Viral genome sequencing methods: benefits and pitfalls of current approaches

Whole genome sequencing of viruses provides high-resolution molecular insights, enhancing our understanding of viral genome function and phylogeny. Beyond fundamental research, viral sequencing is increasingly vital for pathogen surveillance, epidemiology, and clinical applications. As sequencing methods rapidly evolve, the diversity of viral genomics applications and catalogued genomes continues to expand. Advances in long-read, single molecule, real-time sequencing methodologies present opportunities to sequence contiguous, haplotype resolved viral genomes in a range of research and applied settings. Here we present an overview of nucleic acid sequencing methods and their applications in studying viral genomes. We emphasise the advantages of different viral sequencing approaches, with a particular focus on the benefits of third-generation sequencing technologies in elucidating viral evolution, transmission networks, and pathogenesis.

Unveiling the airborne microbial menace: Novel insights into pathogenic bacteria and fungi in bioaerosols from nursery schools to universities

Bacterial and fungal aerosol pollution is widespread in indoor school environments, and poses potential health risks to students and staff. Understanding the distribution and diversity of microbial communities within aerosols is crucial to mitigate their adverse effects. Existing knowledge regarding the composition of bacterial and fungal aerosols, particularly the presence of potential pathogenic microorganisms in fine particulate matter (PM2.5) from nursery schools to universities, is limited. To bridge this knowledge gap, in the present study, we collected PM2.5 samples from five types of schools (i.e., nursery schools, primary schools, junior schools, and high schools and universities) in China. We used advanced single-molecule real-time sequencing to analyze the species-level diversity of bacterial and fungal components in PM2.5 samples based on 16S and ITS ribosomal genes, respectively. We found significant differences in microbial diversity and community composition among the samples obtained from different educational institutions and pollution levels. In particularly, junior schools exhibited higher PM2.5 concentrations (62.2-86.6 μg/m3) than other schools (14.4-48.4 μg/m3). Moreover, microbial variations in PM2.5 samples were associated with institution type. Notably, the prevailing pathogenic microorganisms included Staphylococcus aureus, Staphylococcus epidermidis, Staphylococcus haemolyticus, Streptococcus pneumoniae, and Schizophyllum commune, all of which were identified as Class II Pathogenic Microorganisms in school settings. Four potentially novel strains of S. commune were identified in PM2.5 samples collected from the university; the four strains showed 92.4 %-94.1 % ITS sequence similarity to known Schizophyllum isolates. To the best of our knowledge, this is the first study to explore bacterial and fungal diversity within PM2.5 samples from nursery schools to universities. Overall, these findings contribute to the existing knowledge of school environmental microbiology to ensure the health and safety of students and staff and impacting public health.

EnsembleSeq: a workflow towards real-time, rapid, and simultaneous multi-kingdom-amplicon sequencing for holistic and resource-effective microbiome research at scale

Bacterial communities are often concomitantly present with numerous microorganisms in the human body and other natural environments. Amplicon-based microbiome studies have generally paid skewed attention, that too at a rather shallow genus level resolution, to the highly abundant bacteriome, with interest now forking toward the other microorganisms, particularly fungi. Given the generally sparse abundance of other microbes in the total microbiome, simultaneous sequencing of amplicons targeting multiple microbial kingdoms could be possible even with full multiplexing. Guiding studies are currently needed for performing and monitoring multi-kingdom-amplicon sequencing and data capture at scale. Aiming to address these gaps, amplification of full-length bacterial 16S rRNA gene and entire fungal internal-transcribed spacer (ITS) region was performed for human saliva samples (n = 96, including negative and positive controls). Combined amplicon DNA libraries were prepared for nanopore sequencing using a major fraction of 16S molecules and a minor fraction of ITS amplicons. Sequencing was performed in a single run of an R10.4.1 flow cell employing the latest V14 chemistry. An approach for real-time monitoring of the species saturation using dynamic rarefaction was designed as a guiding determinant of optimal run time. Real-time saturation monitoring for both bacterial and fungal species enabled the completion of sequencing within 30 hours, utilizing less than 60% of the total nanopores. Approximately 5 million high quality (HQ) taxonomically assigned reads were generated (~4.2 million bacterial and 0.7 million fungal), providing a wider (beyond bacteriome) snapshot of human oral microbiota at species-level resolution. Among the more than 400 bacterial and 240 fungal species identified in the studied samples, the species of Streptococcus (e.g., Streptococcus mitis and Streptococcus oralis) and Candida (e.g., Candida albicans and Candida tropicalis) were observed to be the dominating microbes in the oral cavity, respectively. This conformed well with the previous reports of the human oral microbiota. EnsembleSeq provides a proof-of-concept toward the identification of both fungal and bacterial species simultaneously in a single fully multiplexed nanopore sequencing run in a time- and resource-effective manner. Details of this workflow, along with the associated codebase, are provided to enable large-scale application for a holistic species-level microbiome study.

IMPORTANCE

Human microbiome is a sum total of a variety of microbial genomes (including bacteria, fungi, protists, viruses, etc.) present in and on the human body. Yet, a majority of amplicon-based microbiome studies have largely remained skewed toward bacteriome as an assumed proxy of the total microbiome, primarily at a shallow genus level. Cost, time, effort, data quality/management, and importantly lack of guiding studies often limit progress in the direction of moving beyond bacteriome. Here, EnsembleSeq presents a proof-of-concept toward concomitantly capturing multiple-kingdoms of microorganisms (bacteriome and mycobiome) in a fully multiplexed (96-sample) single run of long-read amplicon sequencing. In addition, the workflow captures dynamic tracking of species-level saturation in a time- and resource-effective manner.

Interaction of microbiota, mucosal malignancies, and immunotherapy-Mechanistic insights

The microbiome has emerged as a crucial modulator of host-immune interactions and clearly impacts tumor development and therapy efficacy. The microbiome is a double-edged sword in cancer development and therapy as both pro-tumorigenic and anti-tumorigenic bacterial taxa have been identified. The staggering number of association-based studies in various tumor types has led to an enormous amount of data that makes it difficult to identify bacteria that promote tumor development or modulate therapy efficacy from bystander bacteria. Here we aim to comprehensively summarize the current knowledge of microbiome-host immunity interactions and cancer therapy in various mucosal tissues to find commonalities and thus identify potential functionally relevant bacterial taxa. Moreover, we also review recent studies identifying specific bacteria and mechanisms through which the microbiome modulates cancer development and therapy efficacy.

Application of Next-Generation Sequencing (NGS) Techniques for Selected Companion Animals

Next-Generation Sequencing (NGS) techniques have revolutionized veterinary medicine for cats and dogs, offering insights across various domains. In veterinary parasitology, NGS enables comprehensive profiling of parasite populations, aiding in understanding transmission dynamics and drug resistance mechanisms. In infectious diseases, NGS facilitates rapid pathogen identification, characterization of virulence factors, and tracking of outbreaks. Moreover, NGS sheds light on metabolic processes by elucidating gene expression patterns and metabolic pathways, essential for diagnosing metabolic disorders and designing tailored treatments. In autoimmune diseases, NGS helps identify genetic predispositions and molecular mechanisms underlying immune dysregulation. Veterinary oncology benefits from NGS through personalized tumor profiling, mutation analysis, and identification of therapeutic targets, fostering precision medicine approaches. Additionally, NGS plays a pivotal role in veterinary genetics, unraveling the genetic basis of inherited diseases and facilitating breeding programs for healthier animals. Physiological investigations leverage NGS to explore complex biological systems, unraveling gene-environment interactions and molecular pathways governing health and disease. Application of NGS in treatment planning enhances precision and efficacy by enabling personalized therapeutic strategies tailored to individual animals and their diseases, ultimately advancing veterinary care for companion animals.

Deep mining of antibody phage-display selections using Oxford Nanopore Technologies and Dual Unique Molecular Identifiers

Antibody phage-display technology identifies antibody-antigen interactions through multiple panning rounds, but traditional screening gives no information on enrichment or diversity throughout the process. This results in the loss of valuable binders. Next Generation Sequencing can overcome this problem. We introduce a high accuracy long-read sequencing method based on the recent Oxford Nanopore Technologies (ONT) Q20 + chemistry in combination with dual unique molecular identifiers (UMIs) and an optimized bioinformatic analysis pipeline to monitor the selections. We identified binders from two single-domain antibody libraries selected against a model protein. Traditional colony-picking was compared with our ONT-UMI method. ONT-UMI enabled monitoring of diversity and enrichment before and after each selection round. By combining phage antibody selections with ONT-UMIs, deep mining of output selections is possible. The approach provides an alternative to traditional screening, enabling diversity quantification after each selection round and rare binder recovery, even when the dominating binder was > 99% abundant. Moreover, it can give insights on binding motifs for further affinity maturation and specificity optimizations. Our results demonstrate a platform for future data guided selection strategies.

Enhancing Clinical Utility: Utilization of International Standards and Guidelines for Metagenomic Sequencing in Infectious Disease Diagnosis

Metagenomic sequencing has emerged as a transformative tool in infectious disease diagnosis, offering a comprehensive and unbiased approach to pathogen detection. Leveraging international standards and guidelines is essential for ensuring the quality and reliability of metagenomic sequencing in clinical practice. This review explores the implications of international standards and guidelines for the application of metagenomic sequencing in infectious disease diagnosis. By adhering to established standards, such as those outlined by regulatory bodies and expert consensus, healthcare providers can enhance the accuracy and clinical utility of metagenomic sequencing. The integration of international standards and guidelines into metagenomic sequencing workflows can streamline diagnostic processes, improve pathogen identification, and optimize patient care. Strategies in implementing these standards for infectious disease diagnosis using metagenomic sequencing are discussed, highlighting the importance of standardized approaches in advancing precision infectious disease diagnosis initiatives.

Nanopore DNA sequencing technologies and their applications towards single-molecule proteomics

Sequencing of nucleic acids with nanopores has emerged as a powerful tool offering rapid readout, high accuracy, low cost and portability. This label-free method for sequencing at the single-molecule level is an achievement on its own. However, nanopores also show promise for the technologically even more challenging sequencing of polypeptides, something that could considerably benefit biological discovery, clinical diagnostics and homeland security, as current techniques lack portability and speed. Here we survey the biochemical innovations underpinning commercial and academic nanopore DNA/RNA sequencing techniques, and explore how these advances can fuel developments in future protein sequencing with nanopores.

Bioinformatics identification of potential biomarkers and therapeutic targets for ischemic stroke and vascular dementia

Ischemic stroke and vascular dementia, as common cerebrovascular diseases, with the former causing irreversible neurological damage and the latter causing cognitive and memory impairment, are closely related and have long received widespread attention. Currently, the potential causative genes of these two diseases have yet to be investigated, and effective early diagnostic tools for the diseases have not yet emerged. In this study, we screened new potential biomarkers and analyzed new therapeutic targets for both diseases from the perspective of immune infiltration. Two gene expression profiles on ischemic stroke and vascular dementia were obtained from the NCBI GEO database, and key genes were identified by LASSO regression and SVM-RFE algorithms, and key genes were analyzed by GO and KEGG enrichment. The CIBERSORT algorithm was applied to the gene expression profile species of the two diseases to quantify the 24 subpopulations of immune cells. Moreover, logistic regression modeling analysis was applied to illustrate the stability of the key genes in the diagnosis. Finally, the key genes were validated using RT-PCR assay. A total of 105 intersecting DEGs genes were obtained in the 2 sets of GEO datasets, and bioinformatics functional analysis of the intersecting DEGs genes showed that GO was mainly involved in the purine ribonucleoside triphosphate metabolic process，respiratory chain complex，DNA-binding transcription factor binding and active transmembrane transporter activity. KEGG is mainly involved in the Oxidative phosphorylation, cAMP signaling pathway. The LASSO regression algorithm and SVM-RFE algorithm finally obtained three genes, GAS2L1, ARHGEF40 and PFKFB3, and the logistic regression prediction model determined that the three genes, GAS2L1 (AUC: 0.882), ARHGEF40 (AUC: 0.867) and PFKFB3 (AUC: 0.869), had good diagnostic performance. Meanwhile, the two disease core genes and immune infiltration were closely related, GAS2L1 and PFKFB3 had the highest positive correlation with macrophage M1 (p < 0.001) and the highest negative correlation with mast cell activation (p = 0.0017); ARHGEF40 had the highest positive correlation with macrophage M1 and B cells naive (p < 0.001), the highest negative correlation with B cell memory highest correlation (p = 0.0047). RT-PCR results showed that the relative mRNA expression levels of GAS2L1, ARHGEF40, and PFKFB3 were significantly elevated in the populations of both disease groups (p < 0.05). Immune infiltration-based models can be used to predict the diagnosis of patients with ischemic stroke and vascular dementia and provide a new perspective on the early diagnosis and treatment of both diseases.

Metagenomic profiling of viral and microbial communities from the pox lesions of lumpy skin disease virus and sheeppox virus-infected hosts

Introduction

It has been recognized that capripoxvirus infections have a strong cutaneous tropism with the manifestation of skin lesions in the form of nodules and scabs in the respective hosts, followed by necrosis and sloughing off. Considering that the skin microbiota is a complex community of commensal bacteria, fungi and viruses that are influenced by infections leading to pathological states, there is no evidence on how the skin microbiome is affected during capripoxvirus pathogenesis.

Methods

In this study, shotgun metagenomic sequencing was used to investigate the microbiome in pox lesions from hosts infected with lumpy skin disease virus and sheep pox virus.

Results

The analysis revealed a high degree of variability in bacterial community structures across affected skin samples, indicating the importance of specific commensal microorganisms colonizing individual hosts. The most common and abundant bacteria found in scab samples were Fusobacterium necrophorum, Streptococcus dysgalactiae, Helcococcus ovis and Trueperella pyogenes, irrespective of host. Bacterial reads belonging to the genera Moraxella, Mannheimia, Corynebacterium, Staphylococcus and Micrococcus were identified.

Discussion

This study is the first to investigate capripox virus-associated changes in the skin microbiome using whole-genome metagenomic profiling. The findings will provide a basis for further investigation into capripoxvirus pathogenesis. In addition, this study highlights the challenge of selecting an optimal bioinformatics approach for the analysis of metagenomic data in clinical and veterinary practice. For example, direct classification of reads using a kmer-based algorithm resulted in a significant number of systematic false positives, which may be attributed to the peculiarities of the algorithm and database selection. On the contrary, the process of de novo assembly requires a large number of target reads from the symbiotic microbial community. In this work, the obtained sequencing data were processed by three different approaches, including direct classification of reads based on k-mers, mapping of reads to a marker gene database, and de novo assembly and binning of metagenomic contigs. The advantages and disadvantages of these techniques and their practicality in veterinary settings are discussed in relation to the results obtained.

Research progress on the application of 16S rRNA gene sequencing and machine learning in forensic microbiome individual identification

Forensic microbiome research is a field with a wide range of applications and a number of protocols have been developed for its use in this area of research. As individuals host radically different microbiota, the human microbiome is expected to become a new biomarker for forensic identification. To achieve an effective use of this procedure an understanding of factors which can alter the human microbiome and determinations of stable and changing elements will be critical in selecting appropriate targets for investigation. The 16S rRNA gene, which is notable for its conservation and specificity, represents a potentially ideal marker for forensic microbiome identification. Gene sequencing involving 16S rRNA is currently the method of choice for use in investigating microbiomes. While the sequencing involved with microbiome determinations can generate large multi-dimensional datasets that can be difficult to analyze and interpret, machine learning methods can be useful in surmounting this analytical challenge. In this review, we describe the research methods and related sequencing technologies currently available for application of 16S rRNA gene sequencing and machine learning in the field of forensic identification. In addition, we assess the potential value of 16S rRNA and machine learning in forensic microbiome science.

An integrated method for targeted Oxford Nanopore sequencing and automated bioinformatics for the simultaneous detection of bacteria, fungi, and ARG

AIMS

The use of metagenomics for pathogen identification in clinical practice has been limited. Here we describe a workflow to encourage the clinical utility and potential of NGS for the screening of bacteria, fungi, and antimicrobial resistance genes (ARGs).

METHODS AND RESULTS

The method includes target enrichment, long-read sequencing, and automated bioinformatics. Evaluation of several tools and databases was undertaken across standard organisms (n = 12), clinical isolates (n = 114), and blood samples from patients with suspected bloodstream infections (n = 33). The strategy used could offset the presence of host background DNA, error rates of long-read sequencing, and provide accurate and reproducible detection of pathogens. Eleven targets could be successfully tested in a single assay. Organisms could be confidently identified considering ≥60% of best hits of a BLAST-based threshold of e-value 0.001 and a percent identity of >80%. For ARGs, reads with percent identity of >90% and >60% overlap of the complete gene could be confidently annotated. A kappa of 0.83 was observed compared to standard diagnostic methods. Thus, a workflow for the direct-from-sample, on-site sequencing combined with automated genomics was demonstrated to be reproducible.

CONCLUSION

NGS-based technologies overcome several limitations of current day diagnostics. Highly sensitive and comprehensive methods of pathogen screening are the need of the hour. We developed a framework for reliable, on-site, screening of pathogens.

Multi-omics approaches to studying gastrointestinal microbiome in the context of precision medicine and machine learning

The human gastrointestinal (gut) microbiome plays a critical role in maintaining host health and has been increasingly recognized as an important factor in precision medicine. High-throughput sequencing technologies have revolutionized -omics data generation, facilitating the characterization of the human gut microbiome with exceptional resolution. The analysis of various -omics data, including metatranscriptomics, metagenomics, glycomics, and metabolomics, holds potential for personalized therapies by revealing information about functional genes, microbial composition, glycans, and metabolites. This multi-omics approach has not only provided insights into the role of the gut microbiome in various diseases but has also facilitated the identification of microbial biomarkers for diagnosis, prognosis, and treatment. Machine learning algorithms have emerged as powerful tools for extracting meaningful insights from complex datasets, and more recently have been applied to metagenomics data via efficiently identifying microbial signatures, predicting disease states, and determining potential therapeutic targets. Despite these rapid advancements, several challenges remain, such as key knowledge gaps, algorithm selection, and bioinformatics software parametrization. In this mini-review, our primary focus is metagenomics, while recognizing that other -omics can enhance our understanding of the functional diversity of organisms and how they interact with the host. We aim to explore the current intersection of multi-omics, precision medicine, and machine learning in advancing our understanding of the gut microbiome. A multidisciplinary approach holds promise for improving patient outcomes in the era of precision medicine, as we unravel the intricate interactions between the microbiome and human health.

Comparative transcriptomic analysis of Illumina and MGI next-generation sequencing platforms using RUNX3- and ZBTB46-instructed embryonic stem cells

Introduction: We have previously observed phenotypic and developmental changes upon the ectopic expression of the RUNX3 or the ZBTB46 transcription factors in mouse embryonic stem cell (ESC) derived progenitors. In this study, we evaluated the gene expression profiles of the RUNX3- and the ZBTB46-instructed murine ESCs with RNA-seq testing two next-generation sequencing technologies. Methods: We compared the DNA nanoball-based DNBSEQ G400 sequencer (MGI) with the bridge-PCR-based NextSeq 500 instrument (Illumina) for RNA sequencing. Moreover, we also compared two types of MGI sequencing reagents (Standard versus Hot-massive parallel sequencing (MPS)) with the DNBSEQ G400. Results: We observed that both sequencing platforms showed comparable levels of quality, sequencing uniformity, and gene expression profiles. For example, highly overlapping RUNX3- and ZBTB46-regulated gene lists were obtained from both sequencing datasets. Moreover, we observed that the Standard and the Hot-MPS-derived RUNX3- and ZBTB46-regulated gene lists were also considerably overlapped. This transcriptome analysis also helped us to identify differently expressed genes in the presence of the transgenic RUNX3 or ZBTB46. For example, we found that Gzmb, Gzmd, Gzme, Gdf6, and Ccr7 genes were robustly upregulated upon the forced expression of Runx3; on the other hand, Gpx2, Tdpoz4, and Arg2 were induced alongside the ectopic expression of Zbtb46. Discussion: Similar gene expression profile and greatly overlapping RUNX3- and ZBTB46-regulated gene sets were detected with both DNA sequencing platforms. Our analyses demonstrate that both sequencing technologies are suitable for transcriptome profiling and target gene selection. These findings suggest that DNBSEQ G400 represents a cost-effective alternative sequencing platform for gene expression monitoring. Moreover, this analysis provides a resource for exploration of the RUNX3- and ZBTB46-dependent gene regulatory networks.

The role of oral microbiota in cancer

Cancer remains a significant global challenge, with an estimated 47% increase in cancer patients from 2020 to 2040. Increasing research has identified microorganism as a risk factor for cancer development. The oral cavity, second only to the colon, harbors more than 700 bacterial species and serves as a crucial microbial habitat. Although numerous epidemiological studies have reported associations between oral microorganisms and major systemic tumors, the relationship between oral microorganisms and cancers remains largely unclear. Current research primarily focuses on respiratory and digestive system tumors due to their anatomical proximity to the oral cavity. The relevant mechanism research mainly involves 47% dominant oral microbial population that can be cultured in vitro. However, further exploration is necessary to elucidate the mechanisms underlying the association between oral microbiota and tumors. This review systematically summarizes the reported correlations between oral microbiota and common cancers while also outlining potential mechanisms that may guide biological tumor treatment.

Whole-Genome Sequencing of 502 Individuals from Latvia: The First Step towards a Population-Specific Reference of Genetic Variation

Despite rapid improvements in the accessibility of whole-genome sequencing (WGS), understanding the extent of human genetic variation is limited by the scarce availability of genome sequences from underrepresented populations. Developing the population-scale reference database of Latvian genetic variation may fill the gap in European genomes and improve human genomics research. In this study, we analysed a high-coverage WGS dataset comprising 502 individuals selected from the Genome Database of the Latvian Population. An assessment of variant type, location in the genome, function, medical relevance, and novelty was performed, and a population-specific imputation reference panel (IRP) was developed. We identified more than 18.2 million variants in total, of which 3.3% so far are not represented in gnomAD and dbSNP databases. Moreover, we observed a notable though distinct clustering of the Latvian cohort within the European subpopulations. Finally, our findings demonstrate the improved performance of imputation of variants using the Latvian population-specific reference panel in the Latvian population compared to established IRPs. In summary, our study provides the first WGS data for a regional reference genome that will serve as a resource for the development of precision medicine and complement the global genome dataset, improving the understanding of human genetic variation.

Evaluation of an Adapted Semi-Automated DNA Extraction for Human Salivary Shotgun Metagenomics

Recent attention has highlighted the importance of oral microbiota in human health and disease, e.g., in Parkinson's disease, notably using shotgun metagenomics. One key aspect for efficient shotgun metagenomic analysis relies on optimal microbial sampling and DNA extraction, generally implementing commercial solutions developed to improve sample collection and preservation, and provide high DNA quality and quantity for downstream analysis. As metagenomic studies are today performed on a large number of samples, the next evolution to increase study throughput is with DNA extraction automation. In this study, we proposed a semi-automated DNA extraction protocol for human salivary samples collected with a commercial kit, and compared the outcomes with the DNA extraction recommended by the manufacturer. While similar DNA yields were observed between the protocols, our semi-automated DNA protocol generated significantly higher DNA fragment sizes. Moreover, we showed that the oral microbiome composition was equivalent between DNA extraction methods, even at the species level. This study demonstrates that our semi-automated protocol is suitable for shotgun metagenomic analysis, while allowing for improved sample treatment logistics with reduced technical variability and without compromising the structure of the oral microbiome.

Exploring the Microbiome in Human Reproductive Tract: High-Throughput Methods for the Taxonomic Characterization of Microorganisms

Microorganisms are important due to their widespread presence and multifaceted roles across various domains of life, ecology, and industries. In humans, they underlie the proper functioning of multiple systems crucial to well-being, including immunological and metabolic functions. Emerging research addressing the presence and roles of microorganisms within human reproduction is increasingly relevant. Studies implementing new methodologies (e.g., to investigate vaginal, uterine, and semen microenvironments) can now provide relevant insights into fertility, reproductive health, or pregnancy outcomes. In that sense, cutting-edge sequencing techniques, as well as others such as meta-metabolomics, culturomics, and meta-proteomics, are becoming more popular and accessible worldwide, allowing the characterization of microbiomes at unprecedented resolution. However, they frequently involve rather complex laboratory protocols and bioinformatics analyses, for which researchers may lack the required expertise. A suitable pipeline would successfully enable both taxonomic classification and functional profiling of the microbiome, providing easy-to-understand biological interpretations. However, the selection of an appropriate methodology would be crucial, as it directly impacts the reproducibility, accuracy, and quality of the results and observations. This review focuses on the different current microbiome-related techniques in the context of human reproduction, encompassing niches like vagina, endometrium, and seminal fluid. The most standard and reliable methods are 16S rRNA gene sequencing, metagenomics, and meta-transcriptomics, together with complementary approaches including meta-proteomics, meta-metabolomics, and culturomics. Finally, we also offer case examples and general recommendations about the most appropriate methods and workflows and discuss strengths and shortcomings for each technique.

Comparing genomes recovered from time-series metagenomes using long- and short-read sequencing technologies

BACKGROUND

Over the past years, sequencing technologies have expanded our ability to examine novel microbial metabolisms and diversity previously obscured by isolation approaches. Long-read sequencing promises to revolutionize the metagenomic field and recover less fragmented genomes from environmental samples. Nonetheless, how to best benefit from long-read sequencing and whether long-read sequencing can provide recovered genomes of similar characteristics as short-read approaches remains unclear.

RESULTS

We recovered metagenome-assembled genomes (MAGs) from the free-living fraction at four-time points during a spring bloom in the North Sea. The taxonomic composition of all MAGs recovered was comparable between technologies. However, differences consisted of higher sequencing depth for contigs and higher genome population diversity in short-read compared to long-read metagenomes. When pairing population genomes recovered from both sequencing approaches that shared ≥ 99% average nucleotide identity, long-read MAGs were composed of fewer contigs, a higher N50, and a higher number of predicted genes when compared to short-read MAGs. Moreover, 88% of the total long-read MAGs carried a 16S rRNA gene compared to only 23% of MAGs recovered from short-read metagenomes. Relative abundances for population genomes recovered using both technologies were similar, although disagreements were observed for high and low GC content MAGs.

CONCLUSIONS

Our results highlight that short-read technologies recovered more MAGs and a higher number of species than long-read due to an overall higher sequencing depth. Long-read samples produced higher quality MAGs and similar species composition compared to short-read sequencing. Differences in the GC content recovered by each sequencing technology resulted in divergences in the diversity recovered and relative abundance of MAGs within the GC content boundaries.

In Vitro Modelling of Oral Microbial Invasion in the Human Colon

Recent advances in the human microbiome characterization have revealed significant oral microbial detection in stools of dysbiotic patients. However, little is known about the potential interactions of these invasive oral microorganisms with commensal intestinal microbiota and the host. In this proof-of-concept study, we proposed a new model of oral-to-gut invasion by the combined use of an in vitro model simulating both the physicochemical and microbial (lumen- and mucus-associated microbes) parameters of the human colon (M-ARCOL), a salivary enrichment protocol, and whole-metagenome shotgun sequencing. Oral invasion of the intestinal microbiota was simulated by injection of enriched saliva in the in vitro colon model inoculated with a fecal sample from the same healthy adult donor. The mucosal compartment of M-ARCOL was able to retain the highest species richness levels over time, while species richness levels decreased in the luminal compartment. This study also showed that oral microorganisms preferably colonized the mucosal microenvironment, suggesting potential oral-to-intestinal mucosal competitions. This new model of oral-to-gut invasion can provide useful mechanistic insights into the role of oral microbiome in various disease processes. IMPORTANCE Here, we propose a new model of oral-to-gut invasion by the combined use of an in vitro model simulating both the physicochemical and microbial (lumen- and mucus-associated microbes) parameters of the human colon (M-ARCOL), a salivary enrichment protocol, and whole-metagenome shotgun sequencing. Our study revealed the importance of integrating the mucus compartment, which retained higher microbial richness during fermentation, showed the preference of oral microbial invaders for the mucosal resources, and indicated potential oral-to-intestinal mucosal competitions. It also underlined promising opportunities to further understand mechanisms of oral invasion into the human gut microbiome, define microbe-microbe and mucus-microbe interactions in a compartmentalized fashion, and help to better characterize the potential of oral microbial invasion and their persistence in the gut.

Molecular Detection and Identification of Plant-Associated Lactiplantibacillus plantarum

Lactiplantibacillus plantarum is a lactic acid bacterium often isolated from a wide variety of niches. Its ubiquity can be explained by a large, flexible genome that helps it adapt to different habitats. The consequence of this is great strain diversity, which may make their identification difficult. Accordingly, this review provides an overview of molecular techniques, both culture-dependent, and culture-independent, currently used to detect and identify L. plantarum. Some of the techniques described can also be applied to the analysis of other lactic acid bacteria.

Reliability of species detection in 16S microbiome analysis: Comparison of five widely used pipelines and recommendations for a more standardized approach

The use of NGS-based testing of the bacterial microbiota is often impeded by inconsistent or non-reproducible results, especially when applying different analysis pipelines and reference databases. We investigated five frequently used software packages by submitting the same monobacterial datasets to them, representing the V1-2 and the V3-4 regions of the 16S-rRNA gene of 26 well characterized strains, which were sequenced by the Ion Torrent™ GeneStudio S5 system. The results obtained were divergent and calculations of relative abundance did not yield the expected 100%. We investigated these inconsistencies and were able to attribute them to failures either of the pipelines themselves or of the reference databases they rely on. On the basis of these findings, we recommend certain standards which should help to render microbiome testing more consistent and reproducible, and thus useful in clinical practice.