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Microbial Ecology Jun 2024Forest management influences the occurrence of tree species, the organic matter input to the soil decomposer system, and hence, it can alter soil microbial community and...
Forest management influences the occurrence of tree species, the organic matter input to the soil decomposer system, and hence, it can alter soil microbial community and key ecosystem functions it performs. In this study, we compared the potential effect of different forest management, coppice and high forest, on soil microbial functional diversity, enzyme activities and chemical-physical soil properties in two forests, turkey oak and beech, during summer and autumn. We hypothesized that coppicing influences soil microbial functional diversity with an overall decrease. Contrary to our hypothesis, in summer, the functional diversity of soil microbial community was higher in both coppice forests, suggesting a resilience response of the microbial communities in the soil after tree cutting, which occurred 15-20 years ago. In beech forest under coppice management, a higher content of soil organic matter (but also of soil recalcitrant and stable organic carbon) compared to high forest can explain the higher soil microbial functional diversity and metabolic activity. In turkey oak forest, although differences in functional diversity of soil microbial community between management were observed, for the other investigated parameters, the differences were mainly linked to seasonality. The findings highlight that the soil organic matter preservation depends on the type of forest, but the soil microbial community was able to recover after about 15 years from coppice intervention in both forest ecosystems. Thus, the type of management implemented in these forest ecosystems, not negatively affecting soil organic matter pool, preserving microbial community and potentially soil ecological functions, is sustainable in a scenario of climate change.
Topics: Soil Microbiology; Fagus; Quercus; Forests; Microbiota; Soil; Seasons; Bacteria; Biodiversity; Forestry; Trees; Ecosystem
PubMed: 38940921
DOI: 10.1007/s00248-024-02402-2 -
GigaScience Jan 2024Colletotrichum fungi infect a wide diversity of monocot and dicot hosts, causing diseases on almost all economically important plants worldwide. Colletotrichum is also a...
BACKGROUND
Colletotrichum fungi infect a wide diversity of monocot and dicot hosts, causing diseases on almost all economically important plants worldwide. Colletotrichum is also a suitable model for studying gene family evolution on a fine scale to uncover events in the genome associated with biological changes.
RESULTS
Here we present the genome sequences of 30 Colletotrichum species covering the diversity within the genus. Evolutionary analyses revealed that the Colletotrichum ancestor diverged in the late Cretaceous in parallel with the diversification of flowering plants. We provide evidence of independent host jumps from dicots to monocots during the evolution of Colletotrichum, coinciding with a progressive shrinking of the plant cell wall degradative arsenal and expansions in lineage-specific gene families. Comparative transcriptomics of 4 species adapted to different hosts revealed similarity in gene content but high diversity in the modulation of their transcription profiles on different plant substrates. Combining genomics and transcriptomics, we identified a set of core genes such as specific transcription factors, putatively involved in plant cell wall degradation.
CONCLUSIONS
These results indicate that the ancestral Colletotrichum were associated with dicot plants and certain branches progressively adapted to different monocot hosts, reshaping the gene content and its regulation.
Topics: Colletotrichum; Transcriptome; Genome, Fungal; Evolution, Molecular; Phylogeny; Adaptation, Physiological; Gene Expression Profiling; Plant Diseases
PubMed: 38940768
DOI: 10.1093/gigascience/giae036 -
Bioinformatics (Oxford, England) Jun 2024Shotgun metagenomics allows for direct analysis of microbial community genetics, but scalable computational methods for the recovery of bacterial strain genomes from...
SUMMARY
Shotgun metagenomics allows for direct analysis of microbial community genetics, but scalable computational methods for the recovery of bacterial strain genomes from microbiomes remains a key challenge. We introduce Floria, a novel method designed for rapid and accurate recovery of strain haplotypes from short and long-read metagenome sequencing data, based on minimum error correction (MEC) read clustering and a strain-preserving network flow model. Floria can function as a standalone haplotyping method, outputting alleles and reads that co-occur on the same strain, as well as an end-to-end read-to-assembly pipeline (Floria-PL) for strain-level assembly. Benchmarking evaluations on synthetic metagenomes show that Floria is > 3× faster and recovers 21% more strain content than base-level assembly methods (Strainberry) while being over an order of magnitude faster when only phasing is required. Applying Floria to a set of 109 deeply sequenced nanopore metagenomes took <20 min on average per sample and identified several species that have consistent strain heterogeneity. Applying Floria's short-read haplotyping to a longitudinal gut metagenomics dataset revealed a dynamic multi-strain Anaerostipes hadrus community with frequent strain loss and emergence events over 636 days. With Floria, accurate haplotyping of metagenomic datasets takes mere minutes on standard workstations, paving the way for extensive strain-level metagenomic analyses.
AVAILABILITY AND IMPLEMENTATION
Floria is available at https://github.com/bluenote-1577/floria, and the Floria-PL pipeline is available at https://github.com/jsgounot/Floria_analysis_workflow along with code for reproducing the benchmarks.
Topics: Metagenome; Metagenomics; Haplotypes; Software; Humans; Genome, Bacterial; Microbiota; Bacteria; High-Throughput Nucleotide Sequencing; Sequence Analysis, DNA
PubMed: 38940183
DOI: 10.1093/bioinformatics/btae252 -
Bioinformatics (Oxford, England) Jun 2024World Health Organization estimates that there were over 10 million cases of tuberculosis (TB) worldwide in 2019, resulting in over 1.4 million deaths, with a worrisome...
MOTIVATION
World Health Organization estimates that there were over 10 million cases of tuberculosis (TB) worldwide in 2019, resulting in over 1.4 million deaths, with a worrisome increasing trend yearly. The disease is caused by Mycobacterium tuberculosis (MTB) through airborne transmission. Treatment of TB is estimated to be 85% successful, however, this drops to 57% if MTB exhibits multiple antimicrobial resistance (AMR), for which fewer treatment options are available.
RESULTS
We develop a robust machine-learning classifier using both linear and nonlinear models (i.e. LASSO logistic regression (LR) and random forests (RF)) to predict the phenotypic resistance of Mycobacterium tuberculosis (MTB) for a broad range of antibiotic drugs. We use data from the CRyPTIC consortium to train our classifier, which consists of whole genome sequencing and antibiotic susceptibility testing (AST) phenotypic data for 13 different antibiotics. To train our model, we assemble the sequence data into genomic contigs, identify all unique 31-mers in the set of contigs, and build a feature matrix M, where M[i, j] is equal to the number of times the ith 31-mer occurs in the jth genome. Due to the size of this feature matrix (over 350 million unique 31-mers), we build and use a sparse matrix representation. Our method, which we refer to as MTB++, leverages compact data structures and iterative methods to allow for the screening of all the 31-mers in the development of both LASSO LR and RF. MTB++ is able to achieve high discrimination (F-1 >80%) for the first-line antibiotics. Moreover, MTB++ had the highest F-1 score in all but three classes and was the most comprehensive since it had an F-1 score >75% in all but four (rare) antibiotic drugs. We use our feature selection to contextualize the 31-mers that are used for the prediction of phenotypic resistance, leading to some insights about sequence similarity to genes in MEGARes. Lastly, we give an estimate of the amount of data that is needed in order to provide accurate predictions.
AVAILABILITY
The models and source code are publicly available on Github at https://github.com/M-Serajian/MTB-Pipeline.
Topics: Mycobacterium tuberculosis; Machine Learning; Drug Resistance, Bacterial; Microbial Sensitivity Tests; Anti-Bacterial Agents; Whole Genome Sequencing; Genome, Bacterial; Humans
PubMed: 38940175
DOI: 10.1093/bioinformatics/btae243 -
Bioinformatics (Oxford, England) Jun 2024The study of bacterial genome dynamics is vital for understanding the mechanisms underlying microbial adaptation, growth, and their impact on host phenotype. Structural...
MOTIVATION
The study of bacterial genome dynamics is vital for understanding the mechanisms underlying microbial adaptation, growth, and their impact on host phenotype. Structural variants (SVs), genomic alterations of 50 base pairs or more, play a pivotal role in driving evolutionary processes and maintaining genomic heterogeneity within bacterial populations. While SV detection in isolate genomes is relatively straightforward, metagenomes present broader challenges due to the absence of clear reference genomes and the presence of mixed strains. In response, our proposed method rhea, forgoes reference genomes and metagenome-assembled genomes (MAGs) by encompassing all metagenomic samples in a series (time or other metric) into a single co-assembly graph. The log fold change in graph coverage between successive samples is then calculated to call SVs that are thriving or declining.
RESULTS
We show rhea to outperform existing methods for SV and horizontal gene transfer (HGT) detection in two simulated mock metagenomes, particularly as the simulated reads diverge from reference genomes and an increase in strain diversity is incorporated. We additionally demonstrate use cases for rhea on series metagenomic data of environmental and fermented food microbiomes to detect specific sequence alterations between successive time and temperature samples, suggesting host advantage. Our approach leverages previous work in assembly graph structural and coverage patterns to provide versatility in studying SVs across diverse and poorly characterized microbial communities for more comprehensive insights into microbial gene flux.
AVAILABILITY AND IMPLEMENTATION
rhea is open source and available at: https://github.com/treangenlab/rhea.
Topics: Microbiota; Metagenome; Genome, Bacterial; Metagenomics; Gene Transfer, Horizontal; Bacteria; Algorithms
PubMed: 38940156
DOI: 10.1093/bioinformatics/btae224 -
Systematic Biology Jun 2024Maximum likelihood (ML) phylogenetic inference is widely used in phylogenomics. As heuristic searches most likely find suboptimal trees, it is recommended to conduct...
Maximum likelihood (ML) phylogenetic inference is widely used in phylogenomics. As heuristic searches most likely find suboptimal trees, it is recommended to conduct multiple (e.g., ten) tree searches in phylogenetic analyses. However, beyond its positive role, how and to what extent multiple tree searches aid ML phylogenetic inference remains poorly explored. Here, we found that a random starting tree was not as effective as the BioNJ and parsimony starting trees in inferring ML gene tree and that RAxML-NG and PhyML were less sensitive to different starting trees than IQ-TREE. We then examined the effect of the number of tree searches on ML tree inference with IQ-TREE and RAxML-NG, by running 100 tree searches on 19,414 gene alignments from 15 animal, plant, and fungal phylogenomic datasets. We found that the number of tree searches substantially impacted the recovery of the best-of-100 ML gene tree topology among 100 searches for a given ML program. In addition, all of the concatenation-based trees were topologically identical if the number of tree searches was ≥ 10. Quartet-based ASTRAL trees inferred from 1 to 80 tree searches differed topologically from those inferred from 100 tree searches for 6 /15 phylogenomic datasets. Lastly, our simulations showed that gene alignments with lower difficulty scores had a higher chance of finding the best-of-100 gene tree topology and were more likely to yield the correct trees.
PubMed: 38940001
DOI: 10.1093/sysbio/syae031 -
Frontiers in Cellular and Infection... 2024The rapid detection of Mycobacterium tuberculosis (MTB) is essential for controlling tuberculosis. We designed a portable thermocycler-based real-time fluorescence...
BACKGROUND
The rapid detection of Mycobacterium tuberculosis (MTB) is essential for controlling tuberculosis. We designed a portable thermocycler-based real-time fluorescence loop-mediated isothermal amplification assay (cyp141-RealAmp) using six oligonucleotide primers derived from cyp141 to detect MTB. A combined number of 213 sputum samples (169 obtained from clinically diagnosed cases of pulmonary TB and 44 from a control group without tuberculosis) underwent Acid-fast bacillus (AFB) smear, culture, Xpert MTB/RIF assays, and cyp141-RealAmp assay.
RESULTS
By targeting MTB cyp141, this technique could detect as low as 10 copies/reaction within 30 min, and it was successfully rejected by other mycobacteria and other bacterial species tested. Of the 169 patients, there was no statistical difference between the detection rate of cyp141-RealAmp (92.90%, 95% CI: 89.03-96.07) and that of Xpert MTB/RIF (94.67%, 95% CI: 91.28-98.06) ( > 0.05), but both were statistically higher than that of culture (65.68%, 95% CI: 58.52-72.84) (< 0.05) and AFB (57.40%, 95% CI: 49.94-64.86) (< 0.05). Both cyp141-RealAmp and Xpert MTB/RIF had a specificity of 100%. Furthermore, a high concordance between cyp141-RealAmp and Xpert MTB/RIF was found ( = 0.89).
CONCLUSION
The cyp141-RealAmp assay was shown to be effective, responsive, and accurate in this study. This method offers a prospective strategy for the speedy and precise detection of MTB.
Topics: Mycobacterium tuberculosis; Humans; Nucleic Acid Amplification Techniques; Sensitivity and Specificity; Molecular Diagnostic Techniques; Sputum; Tuberculosis, Pulmonary; DNA Primers; Female; Fluorescence; Adult; Male; Tuberculosis; Middle Aged
PubMed: 38938885
DOI: 10.3389/fcimb.2024.1349063 -
JACS Au Jun 2024This study highlights the novel potential of molecular aggregates as inhibitors of a disease-related protein. Enzyme inhibitors have been studied and developed as...
This study highlights the novel potential of molecular aggregates as inhibitors of a disease-related protein. Enzyme inhibitors have been studied and developed as molecularly targeted drugs and have been applied for cancer, autoimmune diseases, and infections. In many cases, enzyme inhibitors that are used for therapeutic applications interact directly with enzymes in a molecule-to-molecule manner. We found that the aggregates of a small compound, Mn007, inhibited bovine pancreatic DNase I. Once Mn007 molecules formed aggregates, they exhibited inhibitory effects specific to DNases that require divalent metal ions. A DNase secreted by causes streptococcal toxic shock syndrome (STSS). STSS is a severe infectious disease with a fatality rate exceeding 30% in patients, even in this century. disrupts the human barrier system against microbial infections through the secreted DNase. Until now, the discovery/development of a DNase inhibitor has been challenging. Mn007 aggregates were found to inhibit the DNase secreted by , which led to the successful suppression of growth in human whole blood. To date, molecular aggregation has been outside the scope of drug discovery. The present study suggests that molecular aggregation is a vast area to be explored for drug discovery and development because aggregates of small-molecule compounds can inhibit disease-related enzymes.
PubMed: 38938790
DOI: 10.1021/jacsau.4c00210 -
Open Veterinary Journal May 2024infections are considered the most common foodborne pathogens responsible for zoonotic infections and food poisoning in humans and animal species such as birds....
BACKGROUND
infections are considered the most common foodborne pathogens responsible for zoonotic infections and food poisoning in humans and animal species such as birds. Antimicrobial resistance is considered a global anxiety because it causes human public health repercussions, as well as leads to an increase in animal morbidity and death.
AIM
The aims of this study are the isolation and identification of , as well as to investigate the antimicrobial susceptibility test (AST) and the molecular characteristics using polymerase chain reaction (PCR) and sequences for isolates from chicken products (eggs, livers, and minced meat) and human in the Wasit Governorate of Iraq.
METHODS
A total of 300 samples (150 chicken product samples including eggs, livers, and minced meat, and 150 human fecal samples) were collected from the Wasit governorate of Iraq from January to December 2022. The bacterial isolation was done according to recommendations of ISO 6579 standard and the Global Foodborne Infections Network laboratory protocol. Serotyping test and AST were done by using 19 antibiotic agents according to the recommendations of the Clinical and Laboratory Standards Institute, 2022 by using disc diffusion susceptibility test and Vitik 2 test. Finally, the suspected isolates were confirmed using the conventional PCR method and sequencing for a unique gene.
RESULTS
The results showed that the isolation percentage of in chicken products was 8.66% (12% eggs, 6% livers, and 8% minced meat), while in humans it was 4.6%. Also, showed 100% of in humans. While, in chicken eggs , and were 50%, 33.33%, and 16.66%, respectively. Also, showed 100% of in both livers and minced meat. The AST in human isolates showed resistance to Ampicillin, Cefotaxime, Ceftazidime, Cefepime, Amikacin, Gentamicin, Ciprofloxacin, Norfloxacin, and Ceftriaxone, while no resistance to Amoxicillin, Pipracillin, Ertapenem, Imipenem, Meropenem, Fosfomycin, Nitrofurantoin, Trimethoprim, Azithromycin, and Tetracycline. In chicken products, isolates were resistant with different percentages to Amikacin, Gentamicin, Tetracycline, Ciprofloxacin, Norfloxacin, Nitrofurantoin, Ampicillin, Cefotaxime, Ceftazidime, Cefepime, and Trimethoprim; while no resistance to Amoxicillin, Pipracillin, Ertapenem, Imipenem, Meropenem, Fosfomycin, Azithromycin, and Ceftriaxone. Sequencing by using gene was done for four PCR products.
CONCLUSION
This study showed the presence of genetic mutations for which led to variations in the molecular characteristics, and antimicrobial drug resistance of isolated from chicken products and humans.
Topics: Animals; Salmonella enterica; Humans; Chickens; Iraq; Anti-Bacterial Agents; Drug Resistance, Bacterial; Microbial Sensitivity Tests; Meat; Feces; Poultry Products; Salmonella Infections
PubMed: 38938436
DOI: 10.5455/OVJ.2024.v14.i5.5 -
Journal of Microbiology and... Jun 2024The gastrointestinal (GI) tract of shrimp, which is comprised of the stomach, hepatopancreas, and intestine, houses microbial communities that play crucial roles in...
The gastrointestinal (GI) tract of shrimp, which is comprised of the stomach, hepatopancreas, and intestine, houses microbial communities that play crucial roles in immune defense, nutrient absorption, and overall health. While the intestine's microbiome has been well-studied, there has been limited research investigating the stomach and hepatopancreas. The present study addresses this gap by profiling the bacterial community in these interconnected GI segments of Pacific whiteleg shrimp. To this end, shrimp samples were collected from a local aquaculture farm in South Korea, and 16S rRNA gene amplicon sequencing was performed. The results revealed significant variations in bacterial diversity and composition among GI segments. The stomach and hepatopancreas exhibited higher Proteobacteria abundance, while the intestine showed a more diverse microbiome, including Cyanobacteria, Actinobacteria, Bacteroidetes, Firmicutes, Chloroflexi, and Verrucomicrobia. Genera such as , , , , and dominated the intestine, while , , and prevailed in the stomach and hepatopancreas. It is particularly notable that , which is associated with nitrate reduction and pollutant degradation, was prominent in the hepatopancreas. Overall, this study provides insights into the microbial ecology of the Pacific whiteleg shrimp's GI tract, thus enhancing our understanding of shrimp health with the aim of supporting sustainable aquaculture practices.
Topics: Animals; Penaeidae; Hepatopancreas; RNA, Ribosomal, 16S; Bacteria; Gastrointestinal Microbiome; Republic of Korea; Intestines; Phylogeny; Stomach; Biodiversity; Aquaculture; DNA, Bacterial
PubMed: 38938005
DOI: 10.4014/jmb.2403.03039