Hasil untuk "Microbial ecology"

P. Menzel, K. Ng, A. Krogh

Metagenomics emerged as an important field of research not only in microbial ecology but also for human health and disease, and metagenomic studies are performed on increasingly larger scales. While recent taxonomic classification programs achieve high speed by comparing genomic k-mers, they often lack sensitivity for overcoming evolutionary divergence, so that large fractions of the metagenomic reads remain unclassified. Here we present the novel metagenome classifier Kaiju, which finds maximum (in-)exact matches on the protein-level using the Burrows–Wheeler transform. We show in a genome exclusion benchmark that Kaiju classifies reads with higher sensitivity and similar precision compared with current k-mer-based classifiers, especially in genera that are underrepresented in reference databases. We also demonstrate that Kaiju classifies up to 10 times more reads in real metagenomes. Kaiju can process millions of reads per minute and can run on a standard PC. Source code and web server are available at http://kaiju.binf.ku.dk. Here, Anders Krogh and colleagues describe Kaiju, a metagenome taxonomic classification program that uses maximum (in-)exact matches on the protein-level to account for evolutionary divergence. The authors show that Kaiju performs faster and is more sensitive compared with existing algorithms and can be used on a standard computer.

James J Kozich, Sarah L. Westcott, Nielson T. Baxter et al.

J. Cole, Qiong Wang, Jordan A. Fish et al.

Ribosomal Database Project (RDP; http://rdp.cme.msu.edu/) provides the research community with aligned and annotated rRNA gene sequence data, along with tools to allow researchers to analyze their own rRNA gene sequences in the RDP framework. RDP data and tools are utilized in fields as diverse as human health, microbial ecology, environmental microbiology, nucleic acid chemistry, taxonomy and phylogenetics. In addition to aligned and annotated collections of bacterial and archaeal small subunit rRNA genes, RDP now includes a collection of fungal large subunit rRNA genes. RDP tools, including Classifier and Aligner, have been updated to work with this new fungal collection. The use of high-throughput sequencing to characterize environmental microbial populations has exploded in the past several years, and as sequence technologies have improved, the sizes of environmental datasets have increased. With release 11, RDP is providing an expanded set of tools to facilitate analysis of high-throughput data, including both single-stranded and paired-end reads. In addition, most tools are now available as open source packages for download and local use by researchers with high-volume needs or who would like to develop custom analysis pipelines.

Nicholas A. Bokulich, Sathish Subramanian, J. Faith et al.

High-throughput sequencing has revolutionized microbial ecology, but read quality remains a considerable barrier to accurate taxonomy assignment and α-diversity assessment for microbial communities. We demonstrate that high-quality read length and abundance are the primary factors differentiating correct from erroneous reads produced by Illumina GAIIx, HiSeq and MiSeq instruments. We present guidelines for user-defined quality-filtering strategies, enabling efficient extraction of high-quality data and facilitating interpretation of Illumina sequencing results.

J. Gregory Caporaso, K. Bittinger, F. Bushman et al.

Motivation: The Nearest Alignment Space Termination (NAST) tool is commonly used in sequence-based microbial ecology community analysis, but due to the limited portability of the original implementation, it has not been as widely adopted as possible. Python Nearest Alignment Space Termination (PyNAST) is a complete reimplementation of NAST, which includes three convenient interfaces: a Mac OS X GUI, a command-line interface and a simple application programming interface (API). Results: The availability of PyNAST will make the popular NAST algorithm more portable and thereby applicable to datasets orders of magnitude larger by allowing users to install PyNAST on their own hardware. Additionally because users can align to arbitrary template alignments, a feature not available via the original NAST web interface, the NAST algorithm will be readily applicable to novel tasks outside of microbial community analysis. Availability: PyNAST is available at http://pynast.sourceforge.net. Contact: rob.knight@colorado.edu

C. S. Riesenfeld, P. Schloss, J. Handelsman

B. Baker, J. Banfield

T. DeSantis, P. Hugenholtz, N. Larsen et al.

M. Madigan, J. Martinko, J. Parker

U. Sommer, R. Adrian, L. N. D. S. Domis et al.

S. Kembel, Martin Wu, J. Eisen et al.

The abundance of different SSU rRNA (“16S”) gene sequences in environmental samples is widely used in studies of microbial ecology as a measure of microbial community structure and diversity. However, the genomic copy number of the 16S gene varies greatly – from one in many species to up to 15 in some bacteria and to hundreds in some microbial eukaryotes. As a result of this variation the relative abundance of 16S genes in environmental samples can be attributed both to variation in the relative abundance of different organisms, and to variation in genomic 16S copy number among those organisms. Despite this fact, many studies assume that the abundance of 16S gene sequences is a surrogate measure of the relative abundance of the organisms containing those sequences. Here we present a method that uses data on sequences and genomic copy number of 16S genes along with phylogenetic placement and ancestral state estimation to estimate organismal abundances from environmental DNA sequence data. We use theory and simulations to demonstrate that 16S genomic copy number can be accurately estimated from the short reads typically obtained from high-throughput environmental sequencing of the 16S gene, and that organismal abundances in microbial communities are more strongly correlated with estimated abundances obtained from our method than with gene abundances. We re-analyze several published empirical data sets and demonstrate that the use of gene abundance versus estimated organismal abundance can lead to different inferences about community diversity and structure and the identity of the dominant taxa in microbial communities. Our approach will allow microbial ecologists to make more accurate inferences about microbial diversity and abundance based on 16S sequence data.

Huaiyu Ye, Xiaoying Yang, Mingxuan Zheng et al.

Abstract Background Second-generation antipsychotics (SGAs) are increasingly being utilized in children and adolescents. Risperidone, one of the most commonly prescribed SGAs in this population, has been found to adversely affect cognitive function; however, limited knowledge exists regarding the impact of risperidone on the gut microbiome-brain axis. We hypothesized that the cognitive impairment induced by risperidone is mediated by alterations in the gut microbiome and its metabolites. Results In this study, we found that early-life risperidone exposure impaired cognition in mice, including deficits in behavior tests and hippocampal dendritic architecture. The risperidone-exposed mice also exhibited gut microbiota dysbiosis along with damage to the intestinal barrier. Fecal microbiota transplantation (FMT) from treated donors to recipients demonstrated the causal role of the gut microbiome in risperidone-induced cognitive deficits. Of note, risperidone increased the abundance of species Escherichia coli, Eggerthella lenta, Ruminococcus gnavus, Clostridium perfringens, Clostridium difficile, and Blautia hydrogenotrophica. These altered species are identified to encode 7α-HSDH, 3β/α-HSDH, TyrB, and porA, the key enzymes in secondary bile acid metabolism and tyrosine metabolism. Furthermore, a significant reduction in tauroursodeoxycholic acid (TUDCA, the metabolite of bile acid metabolism) and accumulation of p-cresol (the metabolite of tyrosine metabolism) were observed in the brains of mice exposed to risperidone. Mechanically, TUDCA prevented cognitive impairment and endoplasmic reticulum (ER) stress in the hippocampus induced by risperidone, while p-cresol induced neuronal ER stress. Knockout of protein tyrosine phosphatase 1B (PTP1B, ER stress-associated protein) in neurons ameliorated cognitive impairment and neurological damage induced by risperidone. Conclusions This study, for the first time, reveals that early risperidone exposure induces gut microbiome dysbiosis and disturbs the bile acids/tyrosine-PTP1B axis to impair cognitive function. These findings alert the risk of gut and neurological side effects of SGAs treatment and highlight that it is crucial to maintain gut homeostasis during the brain developmental phases of children and adolescents with SGAs exposure. Video Abstract

Sylvia Wenmackers

Philosophers of technology have recently started paying more attention to the environmental impacts of AI, in particular of large language models (LLMs) and generative AI (genAI) applications. Meanwhile, few developers of AI give concrete estimates of the ecological impact of their models and products, and even when they do so, their analysis is often limited to green house gas emissions of certain stages of AI development or use. The current proposal encourages practically viable analyses of the sustainability aspects of genAI informed by philosophical ideas.

Lynsey A. Wilcox Talbot, Nicole L. Vollmer, Anthony Martinez et al.

ABSTRACT The Rice's whale (Balaenoptera ricei) is a critically endangered baleen whale species that resides year‐round in the Gulf of America (formerly the U.S. Gulf of Mexico). The majority of whale sightings occur where the seafloor varies between 100 and 400 m in depth in a restricted region of the northeastern Gulf of America; however, historical whaling records suggest the species may have inhabited other areas and recent acoustic and visual observation data have detected their presence in the northwestern Gulf of America and southwestern Gulf of Mexico. A better understanding of their distribution and movements could aid in this species' recovery. In recent decades, non‐invasive genetic techniques have been developed to detect the presence or absence of species through the use of environmental DNA (eDNA). We developed a quantitative polymerase chain reaction (qPCR) assay targeting the mitochondrial DNA control region to detect eDNA shed by Rice's whales. A rigorous validation process was completed to determine the assay's sensitivity and specificity. The final assay detects low copy numbers of the target eDNA, is highly specific to Rice's whale, and was successfully used to detect the whale's presence in “flukeprint” samples (n = 23). In addition, we tested eDNA collection methods such as filter pore size and the ability to detect Rice's whale eDNA at different time intervals after a whale surfaced and were able to detect eDNA as long as 10 min later. We also used eDNA methods to detect Rice's whale DNA obtained from Acousonde tags after being attached to a whale. Taken together, data from these sampling events will help to refine and improve eDNA collection techniques for many marine mammal species. Future research combining the newly developed eDNA assay with traditional survey methods could improve our understanding of the distribution and habitat use of this endangered and rare species.

Nusrat Ahmad, Mansoor Ahmad Malik, Mohd Yaqub Bhat et al.

Arbuscular mycorrhizal fungi establish vital symbioses with plants that impact development, being a possible strategy in the development of sustainable agriculture. Although there are many different types of medicinal plants in Kashmir Valley, little is known about the native mycoflora's roles, their seasonal and geographical variability in rhizosphere of plants. To understand the mechanism of, which is crucial in regulating the microbial host relationship, a study was carried out across the Kashmir valley to analyze the association of arbuscular mycorhizal fungi with medicinally important plants Valeriana jatamonsi Jones, Lavatera cashmeriana L., and Artemisia absinthium L. During this study plant roots were collected from different areas such as Gulmarg, Sonamarg, Daksum and Kashmir University Botanical Garden (KUBG). The results revealed that the presence of AMF in association with these medicinal plants significantly varied in different areas as well as during different seasons. The maximum root colonization was found during (humidity/wet) summer, and the least root colonization was found during (wet) autumn. A total of thirty-two isolated species of arbuscular mycorrhizal fungi belonging to four genera such as Glomus (n = 15), Acaulospora (n = 10), Scutellospora (n = 5) and Gigaspora (n = 2). The soil samples collected from the rhizosphere also showed considerable variation in chemical parameters, such as soil pH, organic carbon, phosphorous, potassium, and nitrogen levels, which directly affected the associated fungal diversity, spore density, and distribution associated with the plants. The outcome of this study provide valuable insights that can inform future research in microbial ecology, agro ecology, sustainable agriculture, and the development of mycorrhiza-based biofertilizer strategies aimed at enhancing the growth and medicinal value of important plant species.

Chuntao Yin, Shannon L. Osborne, R. Michael Lehman

Introducing cover crops is a conservation practice that diversifies cropping systems and counteracts the detrimental consequences of simplified cropping systems. However, the legacy effects of cover crops on cash crop rhizosphere microbiota are poorly understood. We investigated the response of cash crop rhizosphere microbiota following 5 years of cover crops (winter rye for maize and a mixture of winter rye, forage turnip, clover, Berseem, and Crimson for soybean) introduced into a long-term maize–soybean rotation. Five years of cover crop integration significantly increased the average soybean yields and marginally increased maize yields between 2018 and 2022. Cover crops had significant effects on soybean rhizosphere microbiota selecting bacterial genera within Actinobacteria and Thaumarchaeota phyla and some potentially pathogenic fungi species. There was no significant effect of cover crops on maize rhizosphere microbiota. Cash crop growth stage had consistent, significant effects on both soybean and maize rhizosphere microbiota and accounted for a higher percentage of variation in the rhizosphere microbiota compared with cover crops. Crop growth stage effects were notably strong at the flowering stage for soybean and the seedling stage for maize. The soybean rhizosphere was enriched with nitrogen-fixing bacteria in the flowering stage, whereas the maize rhizosphere recruited a high abundance of plant growth-promoting bacteria in the seedling stage. Cover crops did not significantly improve six selected soil health indicators, with the weak responses linked with cash crop identity. Cover crop legacies may promote beneficial changes in cash crop rhizosphere microbiota, but legacy assessments should account for cash crop identity and growth stage. [Figure: see text] Copyright © 2025 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Joyasree Das, Shilpee Pal, Anu Negi et al.

ABSTRACT Myxobacteria are Gram-negative, spore-forming predatory bacteria isolated from diverse environmental samples that feed on other microbes for their survival and growth. However, no reports of cultured representatives from the human gut have been published to date, although previous investigations have revealed the presence of myxobacterial operational taxonomic units (OTUs) in skin and fecal samples. In this study, three myxobacterial strains designated as O35, O15, and Y35 were isolated and purified from fecal samples of two inflammatory bowel disease (IBD) patients. The 16S rRNA gene sequence analysis and phylogeny identified the strains as Myxococcus spp. belonging to two different clades. Genome-based phylogeny and overall genome-related indices, i.e., average amino acid identity and percentage of conserved proteins, confirmed the heterogeneity within the genus and placed the three strains within two different clades separated at the level of different genera. Digital DNA-DNA hybridization and average nucleotide identity values indicated that they belonged to two novel Myxococcus spp. The analysis of meta-barcoding data from IBD and control cohorts detected OTU lineages closely affiliated to the three novel strains. Based on evidence from detailed structural and functional genomics, we propose the novel species Myxococcus faecalis sp. nov. O35T and a new genus Pseudomyxococcus gen. nov. to accommodate the novel species Pseudomyxococcus flavus sp. nov. Y35T. Overall, these findings provide new information about the occurrence of myxobacteria in the human gut and lay the foundations for a new classification scheme for myxobacterial taxa.IMPORTANCEMyxobacteria have been described from a variety of niches ranging from terrestrial to marine habitats and are known to harbor a diverse portfolio of bioactive molecules. However, to date, there has been no report of isolating culturable representatives from the human gut. This study describes novel myxobacteria from the human gut based on phylogenomics and phenotypic description. The findings are complemented by sequence-based data, wherein operational taxonomic unit (OTU) lineages closely affiliated with the isolated strains have been identified, thus opening a Pandora's box of opportunities for research into the microbial ecology and functional potential of these taxa in the gut ecosystem. Additionally, the study also seeks to establish a new systematic framework, expanding our understanding of myxobacterial taxonomy.

Thomas Van Giel, Aisling J. Daly, Jan M. Baetens et al.

Higher-order interactions (HOIs) have the potential to greatly increase our understanding of ecological interaction networks beyond what is possible with established models that usually consider only pairwise interactions between organisms. While equilibrium values of such HOI-based models have been studied, the dynamics of these models and the stability of their equilibria remain underexplored. Here we present a novel investigation on the effect of the onset speed of a higher-order interaction. In particular, we study the stability of the equilibrium of all configurations of a three-species interaction network, including transitive as well as intransitive ones. We show that the HOI onset speed has a dramatic effect on the evolution and stability of the ecological network, with significant structural changes compared to commonly used HOI extensions or pairwise networks. Changes in the HOI onset speed from fast to slow can reverse the stability of the interaction network. The evolution of the system also affects the equilibrium that will be reached, influenced by the HOI onset speed. This implies that the HOI onset speed is an important determinant in the dynamics of ecological systems, and including it in models of ecological networks can improve our understanding thereof.

Md. Kamrujjaman, Mayesha Sharmim Tisha

In this study, a spatially distributed reaction-diffusion-advection (RDA) model with harvesting is investigated to signify the outcome of a competition between two competing species in a heterogeneous environment. The study builds upon the concept presented in literature \cite{tisha2}, applying it to river ecology in the context of harvesting activities. We assume that despite of having distinct advection and diffusion rates, two species are competing for the same food supply. This paper's main objective is to study, using theoretical and numerical analysis, the global asymptotic stability and coexistence steady state based on different and unequal rates of diffusion and advection. We establish the result for existence, uniqueness and positivity of the solution. The local stability of two semi trivial steady states is demonstrated. Also, we examine the non-existence of coexistence steady state with the help of some non-trivial presumptions. Finally, we combine the local stability with the non-existence of coexistence to demonstrate the global stability using monotone dynamical systems.

Franziska Bauchinger, Franziska Bauchinger, David Seki et al.

Keystone species are thought to play a critical role in determining the structure and function of microbial communities. As they are important candidates for microbiome-targeted interventions, the identification and characterization of keystones is a pressing research goal. Both empirical as well as computational approaches to identify keystones have been proposed, and in particular correlation network analysis is frequently utilized to interrogate sequencing-based microbiome data. Here, we apply an established method for identifying putative keystone taxa in correlation networks. We develop a robust workflow for network construction and systematically evaluate the effects of taxonomic resolution on network properties and the identification of keystone taxa. We are able to identify correlation network keystone species and genera, but could not detect taxa with high keystone potential at lower taxonomic resolution. Based on the correlation patterns observed, we hypothesize that the identified putative keystone taxa have a stabilizing effect that is exerted on correlated taxa. Correlation network analysis further revealed subcommunities present in the dataset that are remarkably similar to previously described patterns. The interrogation of available metatranscriptomes also revealed distinct transcriptional states present in all putative keystone taxa. These results suggest that keystone taxa may have stabilizing properties in a subset of community members rather than global effects. The work presented here contributes to the understanding of correlation network keystone taxa and sheds light on their potential ecological significance.