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Microbiome Feb 2024The recent recognition of the importance of the microbiome to the host's health and well-being has yielded efforts to develop therapies that aim to shift the microbiome...
BACKGROUND
The recent recognition of the importance of the microbiome to the host's health and well-being has yielded efforts to develop therapies that aim to shift the microbiome from a disease-associated state to a healthier one. Direct manipulation techniques of the species' assemblage are currently available, e.g., using probiotics or narrow-spectrum antibiotics to introduce or eliminate specific taxa. However, predicting the species' abundances at the new state remains a challenge, mainly due to the difficulties of deciphering the delicate underlying network of ecological interactions or constructing a predictive model for such complex ecosystems.
RESULTS
Here, we propose a model-free method to predict the species' abundances at the new steady state based on their presence/absence configuration by utilizing a multi-dimensional k-nearest-neighbors (kNN) regression algorithm. By analyzing data from numeric simulations of ecological dynamics, we show that our predictions, which consider the presence/absence of all species holistically, outperform both the null model that uses the statistics of each species independently and a predictive neural network model. We analyze real metagenomic data of human-associated microbial communities and find that by relying on a small number of "neighboring" samples, i.e., samples with similar species assemblage, the kNN predicts the species abundance better than the whole-cohort average. By studying both real metagenomic and simulated data, we show that the predictability of our method is tightly related to the dissimilarity-overlap relationship of the training data.
CONCLUSIONS
Our results demonstrate how model-free methods can prove useful in predicting microbial communities and may facilitate the development of microbial-based therapies. Video Abstract.
Topics: Humans; Microbiota; Metagenome
PubMed: 38303006
DOI: 10.1186/s40168-023-01721-9 -
The ISME Journal Jan 2024Soil ammonia-oxidizing archaea (AOA) play a crucial role in converting ammonia to nitrite, thereby mobilizing reactive nitrogen species into their soluble form, with a...
Soil ammonia-oxidizing archaea (AOA) play a crucial role in converting ammonia to nitrite, thereby mobilizing reactive nitrogen species into their soluble form, with a significant impact on nitrogen losses from terrestrial soils. Yet, our knowledge regarding their diversity and functions remains limited. In this study, we reconstructed 97 high-quality AOA metagenome-assembled genomes (MAGs) from 180 soil samples collected in Central Germany during 2014-2019 summers. These MAGs were affiliated with the order Nitrososphaerales and clustered into four family-level clades (NS-α/γ/δ/ε). Among these MAGs, 75 belonged to the most abundant but least understood δ-clade. Within the δ-clade, the amoA genes in three MAGs from neutral soils showed a 99.5% similarity to the fosmid clone 54d9, which has served as representative of the δ-clade for the past two decades since even today no cultivated representatives are available. Seventy-two MAGs constituted a distinct δ sub-clade, and their abundance and expression activity were more than twice that of other MAGs in slightly acidic soils. Unlike the less abundant clades (α, γ, and ε), the δ-MAGs possessed multiple highly expressed intracellular and extracellular carbohydrate-active enzymes responsible for carbohydrate binding (CBM32) and degradation (GH5), along with highly expressed genes involved in ammonia oxidation. Together, these results suggest metabolic versatility of uncultured soil AOA and a potential mixotrophic or chemolithoheterotrophic lifestyle among 54d9-like AOA.
Topics: Soil Microbiology; Archaea; Ammonia; Oxidation-Reduction; Germany; Metagenome; Phylogeny; Genome, Archaeal; Soil
PubMed: 38742714
DOI: 10.1093/ismejo/wrae086 -
Alzheimer's Research & Therapy Aug 2023Mounting evidence suggests the involvement of viruses in the development and treatment of Alzheimer's disease (AD). However, there remains a significant research gap in...
BACKGROUND
Mounting evidence suggests the involvement of viruses in the development and treatment of Alzheimer's disease (AD). However, there remains a significant research gap in metagenomic studies investigating the gut virome of AD patients, leaving gut viral dysbiosis in AD unexplored. This study aimed to fill this gap by conducting a metagenomics analysis of the gut virome in both amyloid-positive AD patients (Aβ + ADs) and healthy controls (HCs), with the objective of identifying viral signatures linked with AD.
METHOD
Whole-genome sequence (WGS) data from 65 human participants, including 30 Aβ + ADs and 35 HCs, was obtained from the database NCBI SRA (Bio Project: PRJEB47976). The Metaphlan3 pipeline and linear discriminant analysis effect size (LEfSe) analysis were utilized for the bioinformatics process and the detection of viral signatures, respectively. In addition, the Benjamini-Hochberg method was applied with a significance cutoff of 0.05 to evaluate the false discovery rate for all biomarkers identified by LEfSe. The CombiROC model was employed to determine the discriminatory power of the viral signatures identified by LEfSe.
RESULTS
Compared to HCs, the gut virome profiles of Aβ + ADs showed lower alpha diversity, indicating a lower bacteriophage richness. The Siphoviridae family was decreased in Aβ + ADs. Significant decreases of Lactococcus phages were found in Aβ + ADs, including bIL285, Lactococcus phage bIL286, Lactococcus phage bIL309, and Lactococcus phage BK5 T, Lactococcus phage BM13, Lactococcus phage P335 sensu lato, Lactococcus phage phiLC3, Lactococcus phage r1t, Lactococcus phage Tuc2009, Lactococcus phage ul36, and Lactococcus virus bIL67. The predictive combined model of these viral signatures obtained an area under the curve of 0.958 when discriminating Aβ + ADs from HCs.
CONCLUSION
This is the first study to identify distinct viral signatures in the intestine that can be used to effectively distinguish individuals with AD from HCs.
Topics: Humans; Alzheimer Disease; Metagenomics; Amyloidogenic Proteins; Biomarkers; Computational Biology
PubMed: 37608325
DOI: 10.1186/s13195-023-01285-8 -
Emerging Microbes & Infections Dec 2023is a rare and emerging cause of invasive mould infections in patients with haematological malignancies, with a mortality rate of approximately 70%. Here, we present the...
is a rare and emerging cause of invasive mould infections in patients with haematological malignancies, with a mortality rate of approximately 70%. Here, we present the first reported case of suspected disseminated infection in China. The patient experienced a second relapse of acute myeloid leukaemia and developed neutropenia, fever, discrepant blood pressure between limbs, and cutaneous lesions limited to the left upper extremity. Since lung tissue biopsy was not feasible, metagenomic next-generation sequencing (mNGS) and panfungal polymerase chain reaction (PCR) analysis of bronchoalveolar lavage fluid and blood samples were performed, which indicated probable pulmonary infection. Histopathology of cutaneous lesions revealed numerous fungal hyphae within dermal blood vessels. mNGS of a skin biopsy sample identified sequences, and the fungi was subsequently recovered from fungal culture, proving cutaneous infection. Despite combined antifungal therapy, the patient died owing to disease progression. Additionally, 22 previously reported cases of invasive infection were reviewed in patients with haematological malignancies. Thus, mNGS is a powerful diagnostic tool for the early and effective detection of invasive infections, with the advantage of sequencing all potential pathogens, and providing results within 24 h.
Topics: Humans; Lung Diseases, Fungal; Neoplasm Recurrence, Local; Agaricales; Hematologic Neoplasms; High-Throughput Nucleotide Sequencing; Metagenomics; Sensitivity and Specificity
PubMed: 37254739
DOI: 10.1080/22221751.2023.2220581 -
Molecular Systems Biology Sep 2023Multi-omics analyses are used in microbiome studies to understand molecular changes in microbial communities exposed to different conditions. However, it is not always...
Multi-omics analyses are used in microbiome studies to understand molecular changes in microbial communities exposed to different conditions. However, it is not always clear how much each omics data type contributes to our understanding and whether they are concordant with each other. Here, we map the molecular response of a synthetic community of 32 human gut bacteria to three non-antibiotic drugs by using five omics layers (16S rRNA gene profiling, metagenomics, metatranscriptomics, metaproteomics and metabolomics). We find that all the omics methods with species resolution are highly consistent in estimating relative species abundances. Furthermore, different omics methods complement each other for capturing functional changes. For example, while nearly all the omics data types captured that the antipsychotic drug chlorpromazine selectively inhibits Bacteroidota representatives in the community, the metatranscriptome and metaproteome suggested that the drug induces stress responses related to protein quality control. Metabolomics revealed a decrease in oligosaccharide uptake, likely caused by Bacteroidota depletion. Our study highlights how multi-omics datasets can be utilized to reveal complex molecular responses to external perturbations in microbial communities.
Topics: Humans; Multiomics; RNA, Ribosomal, 16S; Microbiota; Metabolomics; Bacteria; Metagenomics
PubMed: 37485738
DOI: 10.15252/msb.202311525 -
Microbial Biotechnology Jan 2024The human microbiome plays a crucial role in maintaining health, with advances in high-throughput sequencing technology and reduced sequencing costs triggering a surge... (Review)
Review
The human microbiome plays a crucial role in maintaining health, with advances in high-throughput sequencing technology and reduced sequencing costs triggering a surge in microbiome research. Microbiome studies generally incorporate five key phases: design, sampling, sequencing, analysis, and reporting, with sequencing strategy being a crucial step offering numerous options. Present mainstream sequencing strategies include Amplicon sequencing, Metagenomic Next-Generation Sequencing (mNGS), and Targeted Next-Generation Sequencing (tNGS). Two innovative technologies recently emerged, namely MobiMicrobe high-throughput microbial single-cell genome sequencing technology and 2bRAD-M simplified metagenomic sequencing technology, compensate for the limitations of mainstream technologies, each boasting unique core strengths. This paper reviews the basic principles and processes of these three mainstream and two novel microbiological technologies, aiding readers in understanding the benefits and drawbacks of different technologies, thereby guiding the selection of the most suitable method for their research endeavours.
Topics: Humans; Microbiota; Metagenome; High-Throughput Nucleotide Sequencing; Metagenomics; Technology
PubMed: 37929823
DOI: 10.1111/1751-7915.14364 -
Poultry Science Oct 2023The gut microbiome plays an important role in quail feed efficiency, immunity, production, and even behavior. Gut microbial gene catalogs and reference genomes are...
The gut microbiome plays an important role in quail feed efficiency, immunity, production, and even behavior. Gut microbial gene catalogs and reference genomes are important for understanding the quail gut microbiome. However, quail gut microbes are lacked sequenced genomes and functional information to date. In this study, we report the first catalog of the microbial genes and metagenome-assembled genomes (MAGs) in fecal and cecum luminal content samples from 3 quail breeds using deep metagenomic sequencing. We identified a total of 2,419,425 nonredundant genes in the quail genome catalog, and a total of 473 MAGs were reconstructed through binning analysis. At 95% average nucleotide identity, the 473 MAGs were clustered into 283 species-level genome bins (SGBs), of which 225 SGBs belonged to species without any available genomes in the current database. Based on the quail gene catalog and MAGs, we identified 142 discriminative bacterial species and 244 discriminative MAGs between Chinese yellow quails and Japanese quails. The discriminative MAGs suggested a strain-level difference in the gut microbial composition. Additionally, a total of 25 Kyoto Encyclopedia of Genes and Genomes functional terms and 88 carbohydrate-active enzymes were distinctly enriched between Chinese yellow quails and Japanese quails. Most of the different species and MAGs were significantly interrelated with the shifts in the functional capacities of the quail gut microbiome. Taken together, we constructed a quail gut microbial gene catalog and enlarged the reference of quail gut microbial genomes. The results of this study provide a powerful and invaluable resource for quail gut microbiome-related research.
Topics: Animals; Metagenome; Gastrointestinal Microbiome; Quail; Chickens; Genes, Microbial
PubMed: 37499616
DOI: 10.1016/j.psj.2023.102931 -
Microbiome Aug 2023There is an increasing interest in investigating the human gut virome for its influence on the gut bacterial community and its putative influence on the trajectory...
BACKGROUND
There is an increasing interest in investigating the human gut virome for its influence on the gut bacterial community and its putative influence on the trajectory towards health or disease. Most gut virome studies are based on sequencing of stored fecal samples. However, relatively little is known about how conventional storage buffers and storage conditions affect the infectivity of bacteriophages and influence the downstream metavirome sequencing.
RESULTS
We demonstrate that the infectivity and genome recovery rate of different spiked bacteriophages (T4, c2 and Phi X174) are variable and highly dependent on storage buffers. Regardless of the storage temperature and timespan, all tested phages immediately lost 100% (DNA/RNA Shield) or more than 90% (StayRNA and RNAlater) of their infectivity. Generally, in SM buffer at 4 °C phage infectivity was preserved for up to 30 days and phage DNA integrity was maintained for up to 100 days. While in CANVAX, the most effective buffer, all spiked phage genomes were preserved for at least 100 days. Prolonged storage time (500 days) at - 80 °C impacted viral diversity differently in the different buffers. Samples stored in CANVAX or DNA/RNA Shield buffer had the least shifts in metavirome composition, after prolonged storage, but they yielded more contigs classified as "uncharacterised". Moreover, in contrast to the SM buffer, these storage buffers yielded a higher fraction of bacterial DNA in metavirome-sequencing libraries. We demonstrated that the latter was due to inactivation of the DNases employed to remove extra-cellular DNA during virome extraction. The latter could be partly avoided by employing additional washing steps prior to virome extraction.
CONCLUSION
Fecal sample storage buffers and storage conditions (time and temperature) strongly influence bacteriophage infectivity and viral composition as determined by plaque assay and metavirome sequencing. The choice of buffer had a larger effect than storage temperature and storage time on the quality of the viral sequences and analyses. Based on these results, we recommend storage of fecal virome samples at in SM buffer at 4 °C for the isolation of viruses and at - 80 °C for metagenomic applications if practically feasible (i.e., access to cold storage). For fecal samples stored in other buffers, samples should be cleared of these buffers before viral extraction and sequencing. Video Abstract.
Topics: Humans; Bacteriophages; DNA, Bacterial; Feces; Metagenome; RNA
PubMed: 37635262
DOI: 10.1186/s40168-023-01632-9 -
Scientific Reports Dec 2023Metagenomics is a powerful tool to study marine microbial communities. However, obtaining high-quality environmental DNA suitable for downstream sequencing applications...
Metagenomics is a powerful tool to study marine microbial communities. However, obtaining high-quality environmental DNA suitable for downstream sequencing applications is a challenging task. The quality and quantity of isolated DNA heavily depend on the choice of purification procedure and the type of sample. Selection of an appropriate DNA isolation method for a new type of material often entails a lengthy trial and error process. Further, each DNA purification approach introduces biases and thus affects the composition of the studied community. To account for these problems and biases, we systematically investigated efficiency of DNA purification from three types of samples (water, sea sediment, and digestive tract of a model invertebrate Magallana gigas) with eight commercially available DNA isolation kits. For each kit-sample combination we measured the quantity of purified DNA, extent of DNA fragmentation, the presence of PCR-inhibiting contaminants, admixture of eukaryotic DNA, alpha-diversity, and reproducibility of the resulting community composition based on 16S rRNA amplicons sequencing. Additionally, we determined a "kitome", e.g., a set of contaminating taxa inherent for each type of purification kit used. The resulting matrix of evaluated parameters allows one to select the best DNA purification procedure for a given type of sample.
Topics: RNA, Ribosomal, 16S; Benchmarking; Reproducibility of Results; DNA; Sequence Analysis, DNA; Metagenomics; DNA, Bacterial
PubMed: 38092853
DOI: 10.1038/s41598-023-48804-z -
NPJ Biofilms and Microbiomes Mar 2024Early dysbiosis in the gut microbiota may contribute to the severity of acute pancreatitis (AP), however, a comprehensive understanding of the gut microbiome, potential...
Early dysbiosis in the gut microbiota may contribute to the severity of acute pancreatitis (AP), however, a comprehensive understanding of the gut microbiome, potential pathobionts, and host metabolome in individuals with AP remains elusive. Hence, we employed fecal whole-metagenome shotgun sequencing in 82 AP patients and 115 matched healthy controls, complemented by untargeted serum metabolome and lipidome profiling in a subset of participants. Analyses of the gut microbiome in AP patients revealed reduced diversity, disrupted microbial functions, and altered abundance of 77 species, influenced by both etiology and severity. AP-enriched species, mostly potential pathobionts, correlated positively with host liver function and serum lipid indicators. Conversely, many AP-depleted species were short-chain fatty acid producers. Gut microflora changes were accompanied by shifts in the serum metabolome and lipidome. Specifically, certain gut species, like enriched Bilophila wadsworthia and depleted Bifidobacterium spp., appeared to contribute to elevated triglyceride levels in biliary or hyperlipidemic AP patients. Through culturing and whole-genome sequencing of bacterial isolates, we identified virulence factors and clinically relevant antibiotic resistance in patient-derived strains, suggesting a predisposition to opportunistic infections. Finally, our study demonstrated that gavage of specific pathobionts could exacerbate pancreatitis in a caerulein-treated mouse model. In conclusion, our comprehensive analysis sheds light on the gut microbiome and serum metabolome in AP, elucidating the role of pathobionts in disease progression. These insights offer valuable perspectives for etiologic diagnosis, prevention, and intervention in AP and related conditions.
Topics: Animals; Mice; Humans; Gastrointestinal Microbiome; Metagenome; Acute Disease; Pancreatitis; RNA, Ribosomal, 16S
PubMed: 38514648
DOI: 10.1038/s41522-024-00499-4